Model Jobs in Jordan

<p><h4>Description</h4> <p>About the opportunity<br> We are hiring on behalf of a major government transformation initiative in Abu Dhabi that is building one of the world’s most ambitious applied AI programs. This organisation is developing the infrastructure and platforms that enable AI-powered public services at scale. The work spans sovereign model serving, vector infrastructure, retrieval systems, developer tooling, and deployment platforms that support critical government applications. This is a rare opportunity to build foundational AI infrastructure with significant real-world impact, in an environment where performance, reliability, and security are mission-critical.</p> <h4>Role overview</h4> <p>We are seeking a Staff AI Platform Engineer to own the platform infrastructure that enables engineering teams to build and operate AI systems efficiently and reliably. This is a senior individual contributor role focused on model serving, vector infrastructure, data pipelines, observability, and deployment platforms. Your success will be measured by the productivity and reliability gains you enable for other engineers.</p> <p>You will combine deep platform engineering expertise with a strong understanding of AI workload requirements, including inference performance, retrieval systems, and operational complexity.</p> <p>At the staff level, you will:</p> <ul> <li>Define and evolve the technical foundations of the AI platform</li> <li>Build systems that accelerate engineering teams across the organisation</li> <li>Set standards for reliability, security, and scalability</li> <li>Lead architecture decisions and evaluate emerging technologies</li> <li>Use AI coding tools such as Codex, Claude Code, or similar as part of your daily workflow</li> </ul> <h4>Key responsibilities</h4> <p><strong>AI platform infrastructure</strong><br> Design and operate model serving infrastructure using vLLM, TGI, TensorRT-LLM, or similar technologies.<br> Build and manage vector infrastructure, embedding pipelines, and retrieval systems.<br> Develop data pipelines for document ingestion, transformation, and storage.<br> Own deployment platforms, CI/CD pipelines, and infrastructure-as-code.</p> <p><strong>Observability & reliability</strong><br> Build observability across the AI stack, including latency, throughput, and model behavior monitoring.<br> Define SLOs, perform capacity planning, and lead reliability engineering initiatives.<br> Lead incident response, root-cause analysis, and postmortems.<br> Establish platform standards for operational excellence.</p> <p><strong>Force multiplication</strong><br> Build reusable internal tooling, SDKs, and deployment patterns.<br> Partner with engineering teams to translate infrastructure needs into scalable platform capabilities.<br> Mentor engineers and raise technical standards across the organisation.</p> <h4>Basic qualifications</h4> <ul> <li>10+ years of platform, infrastructure, or backend engineering experience</li> <li>Proven experience operating at staff or principal engineer level</li> <li>Deep expertise in Azure (AWS or GCP also valued)</li> <li>Strong Kubernetes and Docker experience</li> <li>Hands-on experience with Terraform, CI/CD pipelines, and infrastructure-as-code</li> <li>Experience building production data pipelines</li> <li>Proficiency in Python, Java/Kotlin, or Go</li> <li>Strong PostgreSQL knowledge at production scale</li> <li>Experience with distributed tracing, metrics, logging, and alerting</li> <li>Practical use of AI coding assistants such as Codex or Claude Code</li> <li>Excellent written and verbal communication skills</li> </ul> <h4>Preferred qualifications</h4> <ul> <li>Experience building RAG systems and retrieval infrastructure</li> <li>Experience with LangGraph, LangChain, Semantic Kernel, or similar frameworks</li> <li>Hands-on experience with GPU-based inference infrastructure</li> <li>Experience with vector databases such as pgvector, Qdrant, Pinecone, or Weaviate</li> <li>Familiarity with LLM inference optimization and evaluation frameworks</li> <li>Experience with speech and conversational AI systems</li> <li>Experience building internal developer platforms</li> <li>Security and compliance experience in highly regulated environments</li> </ul> <h4>Technology stack</h4> <p><strong>Backend & platform:</strong> Python, Java, Kotlin, Go, REST, gRPC<br> <strong>AI infrastructure:</strong> vLLM, TGI, TensorRT-LLM, GPU Serving<br> <strong>AI & LLM:</strong> LangChain, LangGraph, Microsoft Agent Framework, vector databases<br> <strong>Data:</strong> PostgreSQL, Redis, DocumentDB, Azure Blob Storage<br> <strong>Infrastructure:</strong> Azure, Docker, Kubernetes, Terraform, CI/CD<br> <strong>Observability:</strong> Langfuse, Grafana, Prometheus, OpenTelemetry<br> <strong>Security:</strong> Entra ID, RBAC, Secrets Management, Zero Trust<br> <strong>AI development:</strong> Codex, Claude Code, OpenCode</p> <h4>What we’re looking for</h4> <p>You are an engineer who:</p> <ul> <li>Thinks in systems and enables others to move faster</li> <li>Designs infrastructure that is reliable, scalable, and easy to operate</li> <li>Grounds technical decisions in evidence and operational data</li> <li>Raises engineering standards through architecture and mentorship</li> <li>Communicates clearly and transparently</li> <li>Embraces AI-native development practices</li> </ul> <h4>Why apply?</h4> <p>This role offers the opportunity to shape the technical foundations of a world-class AI platform supporting transformative public services in Abu Dhabi. You will tackle complex infrastructure challenges at the intersection of AI, cloud computing, and platform engineering while delivering meaningful impact at a national scale.</p></p><p></p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your CV in English and indicate your level of English proficiency.<br> Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.<br> Participation is project-based, not permanent employment.<br>What this opportunity involves: We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<br> You'll create challenging tasks and evaluation criteria within realistic simulated environments: Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history Design tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agent Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust What this is NOT: Not data labeling Not prompt engineering Not writing code from scratch - the agent writes most of the code; you guide and evaluate What we look for: 8+ years in software development Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis Experience writing tests (functional, integration) English proficiency - B2+ Why this is hard: Frontier models are already good at coding.<br> Creating a task that genuinely challenges the best models is non-trivial.<br> You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution.<br> Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<br> How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidEffort estimate Tasks for this project are estimated to take 30 hours to complete, depending on complexity.<br> This is an estimate and not a schedule requirement; you choose when and how to work.<br> Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<br> Compensation: Up to $150/hr equivalent , depending on level and pace.<br> Tasks are estimated at ~30 hours each; you set your own schedule.<br></span> </div>

<p><h4>About Zaincash</h4> <p>ZainCash Iraq is a leading mobile wallet in Iraq and recognized as Forbes top fintech company of 2023 and 2024 as well as GSMA’s best mobile innovation supporting humanitarian situations. The company offers a range of consumer and business services including local and international money transfer, bill payments, companion payment cards, payroll, aid disbursement, and more.</p> <h4>Responsibilities:</h4> <p><strong>1. AI strategy and use case development</strong><br> Identify high-value AI opportunities across customer experience, fraud detection, KYC, operations automation, risk management, compliance, customer support, marketing, analytics, and internal productivity.<br> Work with business and technology stakeholders to evaluate AI ideas based on business value, feasibility, data readiness, cost, risk, and implementation complexity.<br> Build and maintain an AI use case pipeline with clear prioritization, expected impact, ownership, and delivery roadmap.</p> <p><strong>2. Solution design and technical leadership</strong><br> Translate business problems into practical AI solution designs, including LLM-based solutions, RAG, workflow automation, predictive models, document intelligence, image analysis, and intelligent agents.<br> Lead technical evaluation of AI platforms, models, tools, APIs, and vendors.<br> Define the right architecture for each use case, balancing accuracy, cost, latency, security, scalability, and maintainability.<br> Guide engineering teams on AI integration patterns, APIs, model deployment, observability, testing, and production readiness.</p> <p><strong>3. Proof of concept and production delivery</strong><br> Lead AI proof of concepts from problem framing to testing and business validation.<br> Define success metrics for each AI use case, including accuracy, automation rate, cost saving, fraud reduction, customer experience improvement, or operational efficiency.<br> Ensure successful use cases are transitioned from PoC to production with proper governance, monitoring, documentation, and support model.<br> Avoid AI for the sake of AI by ensuring every solution has a clear business case and measurable value.</p> <p><strong>4. AI governance, risk, and compliance</strong><br> Establish practical AI governance standards covering data privacy, security, responsible AI, model risk, explainability, auditability, and human-in-the-loop controls.<br> Work with information security, risk, compliance, legal, and internal audit to ensure AI solutions are aligned with regulatory and internal control requirements.<br> Evaluate AI solutions for data leakage, hallucination risk, bias, misuse, operational risk, and vendor dependency.<br> Define approval gates for AI use cases before they are deployed into production.</p> <p><strong>5. Data and platform readiness</strong><br> Assess the availability, quality, and accessibility of data required for AI use cases.<br> Work with data, application, infrastructure, and security teams to improve AI readiness across ZainCash platforms.<br> Support the creation of reusable AI capabilities, such as document processing, knowledge search, customer support assistants, fraud signals, workflow automation, and internal copilots.<br> Promote reusable patterns instead of isolated experiments.</p> <p><strong>6. Vendor and partner evaluation</strong><br> Evaluate AI vendors, cloud AI services, local models, open source frameworks, and specialized fintech AI solutions.<br> Run structured vendor assessments covering technical fit, security, data residency, cost, integration effort, support, and long-term sustainability.<br> Support procurement and management in making informed build versus buy decisions.</p> <p><strong>7. Team enablement and knowledge sharing</strong><br> Mentor engineers, analysts, product owners, and business teams on practical AI usage.<br> Create awareness sessions, internal guidelines, and reusable templates for AI opportunity assessment.<br> Support the development of internal AI capabilities and reduce dependency on external vendors where possible.</p> <h4>Requirements</h4> <p>Bachelor degree in computer science, software engineering, data science, AI, or a related technical field.<br> 8 plus years of overall technology experience, with at least 3 years in AI, machine learning, data science, or advanced analytics.<br> Strong hands-on understanding of modern AI concepts, including LLMs, RAG, embeddings, prompt engineering, AI agents, computer vision, document AI, predictive analytics, and MLOps.<br> Strong software engineering background, preferably with Python and API-based system integration.<br> Experience designing and delivering production grade AI or data-driven solutions.<br> Good understanding of cloud AI services, managed ML platforms, open source AI frameworks, and model deployment approaches.<br> Strong understanding of data privacy, security, responsible AI, and model governance.<br> Ability to communicate clearly with both technical and non-technical stakeholders.<br> Strong problem solving skills and ability to challenge unclear or low-value AI ideas.</p> <h4>Preferred qualifications:</h4> <li>Experience in fintech, banking, payments, telecom, financial services, or regulated industries.</li> <li>Experience with fraud detection, KYC automation, AML support, customer service automation, or transaction analytics.</li> <li>Experience with Arabic language AI use cases, OCR, document processing, or image-based verification.</li> <li>Experience with OpenShift, Kubernetes, microservices, API gateways, CI/CD, and enterprise integration.</li> <li>Experience evaluating AI vendors and preparing business cases for technology investment.</li> <li>Knowledge of data platforms, data pipelines, BI, and analytics environments.</li></p><p></p>

<p><h4>About Zaincash</h4> <p>ZainCash Iraq is a leading mobile wallet in Iraq and recognized as Forbes top fintech company of 2023 and 2024 as well as GSMA’s best mobile innovation supporting humanitarian situations. The company offers a range of consumer and business services including local and international money transfer, bill payments, companion payment cards, payroll, aid disbursement, and more.</p> <h4>Responsibilities:</h4> <p><strong>1. AI strategy and use case development</strong><br> Identify high-value AI opportunities across customer experience, fraud detection, KYC, operations automation, risk management, compliance, customer support, marketing, analytics, and internal productivity.<br> Work with business and technology stakeholders to evaluate AI ideas based on business value, feasibility, data readiness, cost, risk, and implementation complexity.<br> Build and maintain an AI use case pipeline with clear prioritization, expected impact, ownership, and delivery roadmap.</p> <p><strong>2. Solution design and technical leadership</strong><br> Translate business problems into practical AI solution designs, including LLM-based solutions, RAG, workflow automation, predictive models, document intelligence, image analysis, and intelligent agents.<br> Lead technical evaluation of AI platforms, models, tools, APIs, and vendors.<br> Define the right architecture for each use case, balancing accuracy, cost, latency, security, scalability, and maintainability.<br> Guide engineering teams on AI integration patterns, APIs, model deployment, observability, testing, and production readiness.</p> <p><strong>3. Proof of concept and production delivery</strong><br> Lead AI proof of concepts from problem framing to testing and business validation.<br> Define success metrics for each AI use case, including accuracy, automation rate, cost saving, fraud reduction, customer experience improvement, or operational efficiency.<br> Ensure successful use cases are transitioned from PoC to production with proper governance, monitoring, documentation, and support model.<br> Avoid AI for the sake of AI by ensuring every solution has a clear business case and measurable value.</p> <p><strong>4. AI governance, risk, and compliance</strong><br> Establish practical AI governance standards covering data privacy, security, responsible AI, model risk, explainability, auditability, and human-in-the-loop controls.<br> Work with information security, risk, compliance, legal, and internal audit to ensure AI solutions are aligned with regulatory and internal control requirements.<br> Evaluate AI solutions for data leakage, hallucination risk, bias, misuse, operational risk, and vendor dependency.<br> Define approval gates for AI use cases before they are deployed into production.</p> <p><strong>5. Data and platform readiness</strong><br> Assess the availability, quality, and accessibility of data required for AI use cases.<br> Work with data, application, infrastructure, and security teams to improve AI readiness across ZainCash platforms.<br> Support the creation of reusable AI capabilities, such as document processing, knowledge search, customer support assistants, fraud signals, workflow automation, and internal copilots.<br> Promote reusable patterns instead of isolated experiments.</p> <p><strong>6. Vendor and partner evaluation</strong><br> Evaluate AI vendors, cloud AI services, local models, open source frameworks, and specialized fintech AI solutions.<br> Run structured vendor assessments covering technical fit, security, data residency, cost, integration effort, support, and long-term sustainability.<br> Support procurement and management in making informed build versus buy decisions.</p> <p><strong>7. Team enablement and knowledge sharing</strong><br> Mentor engineers, analysts, product owners, and business teams on practical AI usage.<br> Create awareness sessions, internal guidelines, and reusable templates for AI opportunity assessment.<br> Support the development of internal AI capabilities and reduce dependency on external vendors where possible.</p> <h4>Requirements</h4> <p>Bachelor degree in computer science, software engineering, data science, AI, or a related technical field.<br> 8 plus years of overall technology experience, with at least 3 years in AI, machine learning, data science, or advanced analytics.<br> Strong hands-on understanding of modern AI concepts, including LLMs, RAG, embeddings, prompt engineering, AI agents, computer vision, document AI, predictive analytics, and MLOps.<br> Strong software engineering background, preferably with Python and API-based system integration.<br> Experience designing and delivering production grade AI or data-driven solutions.<br> Good understanding of cloud AI services, managed ML platforms, open source AI frameworks, and model deployment approaches.<br> Strong understanding of data privacy, security, responsible AI, and model governance.<br> Ability to communicate clearly with both technical and non-technical stakeholders.<br> Strong problem solving skills and ability to challenge unclear or low-value AI ideas.</p> <h4>Preferred qualifications:</h4> <li>Experience in fintech, banking, payments, telecom, financial services, or regulated industries.</li> <li>Experience with fraud detection, KYC automation, AML support, customer service automation, or transaction analytics.</li> <li>Experience with Arabic language AI use cases, OCR, document processing, or image-based verification.</li> <li>Experience with OpenShift, Kubernetes, microservices, API gateways, CI/CD, and enterprise integration.</li> <li>Experience evaluating AI vendors and preparing business cases for technology investment.</li> <li>Knowledge of data platforms, data pipelines, BI, and analytics environments.</li></p><p></p>

<p><h4>About Zaincash</h4> <p>ZainCash Iraq is a leading mobile wallet in Iraq and recognized as Forbes top fintech company of 2023 and 2024 as well as GSMA’s best mobile innovation supporting humanitarian situations. The company offers a range of consumer and business services including local and international money transfer, bill payments, companion payment cards, payroll, aid disbursement, and more.</p> <h4>Responsibilities:</h4> <p><strong>1. AI strategy and use case development</strong><br> Identify high value AI opportunities across customer experience, fraud detection, KYC, operations automation, risk management, compliance, customer support, marketing, analytics, and internal productivity.<br> Work with business and technology stakeholders to evaluate AI ideas based on business value, feasibility, data readiness, cost, risk, and implementation complexity.<br> Build and maintain an AI use case pipeline with clear prioritization, expected impact, ownership, and delivery roadmap.</p> <p><strong>2. Solution design and technical leadership</strong><br> Translate business problems into practical AI solution designs, including LLM based solutions, RAG, workflow automation, predictive models, document intelligence, image analysis, and intelligent agents.<br> Lead technical evaluation of AI platforms, models, tools, APIs, and vendors.<br> Define the right architecture for each use case, balancing accuracy, cost, latency, security, scalability, and maintainability.<br> Guide engineering teams on AI integration patterns, APIs, model deployment, observability, testing, and production readiness.</p> <p><strong>3. Proof of concept and production delivery</strong><br> Lead AI proof of concepts from problem framing to testing and business validation.<br> Define success metrics for each AI use case, including accuracy, automation rate, cost saving, fraud reduction, customer experience improvement, or operational efficiency.<br> Ensure successful use cases are transitioned from PoC to production with proper governance, monitoring, documentation, and support model.<br> Avoid AI for the sake of AI by ensuring every solution has a clear business case and measurable value.</p> <p><strong>4. AI governance, risk, and compliance</strong><br> Establish practical AI governance standards covering data privacy, security, responsible AI, model risk, explainability, auditability, and human in the loop controls.<br> Work with information security, risk, compliance, legal, and internal audit to ensure AI solutions are aligned with regulatory and internal control requirements.<br> Evaluate AI solutions for data leakage, hallucination risk, bias, misuse, operational risk, and vendor dependency.<br> Define approval gates for AI use cases before they are deployed into production.</p> <p><strong>5. Data and platform readiness</strong><br> Assess the availability, quality, and accessibility of data required for AI use cases.<br> Work with data, application, infrastructure, and security teams to improve AI readiness across ZainCash platforms.<br> Support the creation of reusable AI capabilities, such as document processing, knowledge search, customer support assistants, fraud signals, workflow automation, and internal copilots.<br> Promote reusable patterns instead of isolated experiments.</p> <p><strong>6. Vendor and partner evaluation</strong><br> Evaluate AI vendors, cloud AI services, local models, open source frameworks, and specialized fintech AI solutions.<br> Run structured vendor assessments covering technical fit, security, data residency, cost, integration effort, support, and long term sustainability.<br> Support procurement and management in making informed build versus buy decisions.</p> <p><strong>7. Team enablement and knowledge sharing</strong><br> Mentor engineers, analysts, product owners, and business teams on practical AI usage.<br> Create awareness sessions, internal guidelines, and reusable templates for AI opportunity assessment.<br> Support the development of internal AI capabilities and reduce dependency on external vendors where possible.</p> <h4>Requirements</h4> <p>Bachelor degree in computer science, software engineering, data science, AI, or a related technical field.<br> 8-plus years of overall technology experience, with at least 3 years in AI, machine learning, data science, or advanced analytics.<br> Strong hands-on understanding of modern AI concepts, including LLMs, RAG, embeddings, prompt engineering, AI agents, computer vision, document AI, predictive analytics, and MLOps.<br> Strong software engineering background, preferably with Python and API based system integration.<br> Experience designing and delivering production grade AI or data driven solutions.<br> Good understanding of cloud AI services, managed ML platforms, open source AI frameworks, and model deployment approaches.<br> Strong understanding of data privacy, security, responsible AI, and model governance.<br> Ability to communicate clearly with both technical and non-technical stakeholders.<br> Strong problem solving skills and ability to challenge unclear or low value AI ideas.</p> <h4>Preferred qualifications:</h4> <ul> <li>Experience in fintech, banking, payments, telecom, financial services, or regulated industries.</li> <li>Experience with fraud detection, KYC automation, AML support, customer service automation, or transaction analytics.</li> <li>Experience with Arabic language AI use cases, OCR, document processing, or image based verification.</li> <li>Experience with OpenShift, Kubernetes, microservices, API gateways, CI/CD, and enterprise integration.</li> <li>Experience evaluating AI vendors and preparing business cases for technology investment.</li> <li>Knowledge of data platforms, data pipelines, BI, and analytics environments.</li> </ul></p><p></p>

<p><h4>About Zaincash</h4> <p>ZainCash Iraq is a leading mobile wallet in Iraq and recognized as Forbes top fintech company of 2023 and 2024 as well as GSMA’s best mobile innovation supporting humanitarian situations. The company offers a range of consumer and business services including local and international money transfer, bill payments, companion payment cards, payroll, aid disbursement, and more.</p> <h4>Responsibilities:</h4> <p><strong>1. AI strategy and use case development</strong><br> Identify high value AI opportunities across customer experience, fraud detection, KYC, operations automation, risk management, compliance, customer support, marketing, analytics, and internal productivity.<br> Work with business and technology stakeholders to evaluate AI ideas based on business value, feasibility, data readiness, cost, risk, and implementation complexity.<br> Build and maintain an AI use case pipeline with clear prioritization, expected impact, ownership, and delivery roadmap.</p> <p><strong>2. Solution design and technical leadership</strong><br> Translate business problems into practical AI solution designs, including LLM based solutions, RAG, workflow automation, predictive models, document intelligence, image analysis, and intelligent agents.<br> Lead technical evaluation of AI platforms, models, tools, APIs, and vendors.<br> Define the right architecture for each use case, balancing accuracy, cost, latency, security, scalability, and maintainability.<br> Guide engineering teams on AI integration patterns, APIs, model deployment, observability, testing, and production readiness.</p> <p><strong>3. Proof of concept and production delivery</strong><br> Lead AI proof of concepts from problem framing to testing and business validation.<br> Define success metrics for each AI use case, including accuracy, automation rate, cost saving, fraud reduction, customer experience improvement, or operational efficiency.<br> Ensure successful use cases are transitioned from PoC to production with proper governance, monitoring, documentation, and support model.<br> Avoid AI for the sake of AI by ensuring every solution has a clear business case and measurable value.</p> <p><strong>4. AI governance, risk, and compliance</strong><br> Establish practical AI governance standards covering data privacy, security, responsible AI, model risk, explainability, auditability, and human in the loop controls.<br> Work with information security, risk, compliance, legal, and internal audit to ensure AI solutions are aligned with regulatory and internal control requirements.<br> Evaluate AI solutions for data leakage, hallucination risk, bias, misuse, operational risk, and vendor dependency.<br> Define approval gates for AI use cases before they are deployed into production.</p> <p><strong>5. Data and platform readiness</strong><br> Assess the availability, quality, and accessibility of data required for AI use cases.<br> Work with data, application, infrastructure, and security teams to improve AI readiness across ZainCash platforms.<br> Support the creation of reusable AI capabilities, such as document processing, knowledge search, customer support assistants, fraud signals, workflow automation, and internal copilots.<br> Promote reusable patterns instead of isolated experiments.</p> <p><strong>6. Vendor and partner evaluation</strong><br> Evaluate AI vendors, cloud AI services, local models, open source frameworks, and specialized fintech AI solutions.<br> Run structured vendor assessments covering technical fit, security, data residency, cost, integration effort, support, and long term sustainability.<br> Support procurement and management in making informed build versus buy decisions.</p> <p><strong>7. Team enablement and knowledge sharing</strong><br> Mentor engineers, analysts, product owners, and business teams on practical AI usage.<br> Create awareness sessions, internal guidelines, and reusable templates for AI opportunity assessment.<br> Support the development of internal AI capabilities and reduce dependency on external vendors where possible.</p> <h4>Requirements</h4> <p>Bachelor degree in computer science, software engineering, data science, AI, or a related technical field.<br> 8-plus years of overall technology experience, with at least 3 years in AI, machine learning, data science, or advanced analytics.<br> Strong hands-on understanding of modern AI concepts, including LLMs, RAG, embeddings, prompt engineering, AI agents, computer vision, document AI, predictive analytics, and MLOps.<br> Strong software engineering background, preferably with Python and API based system integration.<br> Experience designing and delivering production grade AI or data driven solutions.<br> Good understanding of cloud AI services, managed ML platforms, open source AI frameworks, and model deployment approaches.<br> Strong understanding of data privacy, security, responsible AI, and model governance.<br> Ability to communicate clearly with both technical and non-technical stakeholders.<br> Strong problem solving skills and ability to challenge unclear or low value AI ideas.</p> <h4>Preferred qualifications:</h4> <ul> <li>Experience in fintech, banking, payments, telecom, financial services, or regulated industries.</li> <li>Experience with fraud detection, KYC automation, AML support, customer service automation, or transaction analytics.</li> <li>Experience with Arabic language AI use cases, OCR, document processing, or image based verification.</li> <li>Experience with OpenShift, Kubernetes, microservices, API gateways, CI/CD, and enterprise integration.</li> <li>Experience evaluating AI vendors and preparing business cases for technology investment.</li> <li>Knowledge of data platforms, data pipelines, BI, and analytics environments.</li> </ul></p><p></p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>About Zaincash ZainCash Iraq is a leading mobile wallet in Iraq and recognized as Forbes top Fintech company of 2023 and 2024 as well as GSMA’s Best Mobile Innovation Supporting Humanitarian Situations.<br> The company offers a range of consumer and business services including local and international money transfer, bill payments, companion payment cards, payroll, aid disbursement, and more.<br> For more information, please visit www.<br>zaincash.iq. Responsibilities: 1.<br> AI Strategy and Use Case Development Identify high value AI opportunities across customer experience, fraud detection, KYC, operations automation, risk management, compliance, customer support, marketing, analytics, and internal productivity.<br> Work with business and technology stakeholders to evaluate AI ideas based on business value, feasibility, data readiness, cost, risk, and implementation complexity.<br> Build and maintain an AI use case pipeline with clear prioritization, expected impact, ownership, and delivery roadmap.<br> 2. Solution Design and Technical Leadership Translate business problems into practical AI solution designs, including LLM based solutions, RAG, workflow automation, predictive models, document intelligence, image analysis, and intelligent agents.<br> Lead technical evaluation of AI platforms, models, tools, APIs, and vendors.<br> Define the right architecture for each use case, balancing accuracy, cost, latency, security, scalability, and maintainability.<br> Guide engineering teams on AI integration patterns, APIs, model deployment, observability, testing, and production readiness.<br> 3. Proof of Concept and Production Delivery Lead AI proof of concepts from problem framing to testing and business validation.<br> Define success metrics for each AI use case, including accuracy, automation rate, cost saving, fraud reduction, customer experience improvement, or operational efficiency.<br> Ensure successful use cases are transitioned from PoC to production with proper governance, monitoring, documentation, and support model.<br> Avoid AI for the sake of AI by ensuring every solution has a clear business case and measurable value.<br> 4. AI Governance, Risk, and Compliance Establish practical AI governance standards covering data privacy, security, responsible AI, model risk, explainability, auditability, and human in the loop controls.<br> Work with Information Security, Risk, Compliance, Legal, and Internal Audit to ensure AI solutions are aligned with regulatory and internal control requirements.<br> Evaluate AI solutions for data leakage, hallucination risk, bias, misuse, operational risk, and vendor dependency.<br> Define approval gates for AI use cases before they are deployed into production.<br> 5. Data and Platform Readiness Assess the availability, quality, and accessibility of data required for AI use cases.<br> Work with data, application, infrastructure, and security teams to improve AI readiness across ZainCash platforms.<br> Support the creation of reusable AI capabilities, such as document processing, knowledge search, customer support assistants, fraud signals, workflow automation, and internal copilots.<br> Promote reusable patterns instead of isolated experiments.<br> 6. Vendor and Partner Evaluation Evaluate AI vendors, cloud AI services, local models, open source frameworks, and specialized fintech AI solutions.<br> Run structured vendor assessments covering technical fit, security, data residency, cost, integration effort, support, and long term sustainability.<br> Support procurement and management in making informed build versus buy decisions.<br> 7. Team Enablement and Knowledge Sharing Mentor engineers, analysts, product owners, and business teams on practical AI usage.<br> Create awareness sessions, internal guidelines, and reusable templates for AI opportunity assessment.<br> Support the development of internal AI capabilities and reduce dependency on external vendors where possible.<br> Bachelor degree in Computer Science, Software Engineering, Data Science, AI, or a related technical field.<br> 8 plus years of overall technology experience, with at least 3 years in AI, machine learning, data science, or advanced analytics.<br> Strong hands on understanding of modern AI concepts, including LLMs, RAG, embeddings, prompt engineering, AI agents, computer vision, document AI, predictive analytics, and MLOps.<br> Strong software engineering background, preferably with Python and API based system integration.<br> Experience designing and delivering production grade AI or data driven solutions.<br> Good understanding of cloud AI services, managed ML platforms, open source AI frameworks, and model deployment approaches.<br> Strong understanding of data privacy, security, responsible AI, and model governance.<br> Ability to communicate clearly with both technical and non technical stakeholders.<br> Strong problem solving skills and ability to challenge unclear or low value AI ideas.<br> Preferred Qualifications: Experience in fintech, banking, payments, telecom, financial services, or regulated industries.<br> Experience with fraud detection, KYC automation, AML support, customer service automation, or transaction analytics.<br> Experience with Arabic language AI use cases, OCR, document processing, or image based verification.<br> Experience with OpenShift, Kubernetes, microservices, API gateways, CI/CD, and enterprise integration.<br> Experience evaluating AI vendors and preparing business cases for technology investment.<br> Knowledge of data platforms, data pipelines, BI, and analytics environments.<br></span> </div>

<p>Responsibilities Develop, localize, test, and continuously improve AI services for the MENA region. Evaluate AI system and model performance and identify areas for improvement. Develop and improve NLP/NLU, speech, and conversational AI solutions. Collect, prepare, organize, and maintain multilingual datasets for AI training, testing, and evaluation. Develop tools and automation for data processing, model evaluation, and performance analysis. Identify and address language- and region-specific challenges related to AI services. Analyze data and system performance to improve the quality and accuracy of AI solutions. Collaborate with technical and cross-functional teams to deliver high-quality localized AI experiences.</p><p><strong>Desired Candidate Profile</strong></p><p>Qualifications Bachelor s degree in Computer Science, Computer Engineering, or a related technical field. 3 6 years of relevant professional experience in AI, NLP, Machine Learning, Software Engineering, or a related field. Strong programming fundamentals, preferably in Python, C/C++, or Java. Experience with Linux, shell scripting, and Git. Good understanding of data structures, algorithms, and machine learning/deep learning fundamentals. Experience with PyTorch or TensorFlow is preferred. Good understanding of NLP/NLU concepts, including text preprocessing, tokenization, intent classification, and related techniques. Proficiency in both Arabic and English. Strong analytical and problem-solving skills. Ability to work effectively with technical and cross-functional teams. Required Skills Analytical Skills Linux Data Structure Python Automation Git C++ AI</p>

<p>The consultancy will contribute to: A clear institutional framework for GBV prevention and response across UNRWA. GBV prevention and response Programme model with guidance on context adaptation Defined roles and responsibilities across programmes and Fields of Operation. Programme-specific GBV commitments integrated within existing programme systems and operational procedures. Strengthened coordination, accountability and referral systems. Improved analysis of GBV risks and vulnerabilities. More consistent and survivor-centered services for Palestine refugees. Enhanced capacity for evidence-based decision-making and monitoring.</p><p>Work Location Home-based with virtual consultations and meetings.</p><p>Expected duration The duration of the consultancy is 3 months (01 October 2026- 31 Dec 2026).</p><p>The consultant will undertake the following tasks:</p><p>Deliverable 1: Inception Phase</p><ul><li>Conduct a desk review of relevant UNRWA policies, strategies, guidance, tools and standard operating procedures related to GBV prevention and response.</li><li>Develop an inception report outlining the methodology, workplan, consultation approach and timeline for the assignment.</li></ul><p>Deliverable: Inception report and workplan</p><p>Deliverable 2: Mapping and Institutional Assessment</p><ul><li>Map existing internal GBV-related capacities, systems, internal services, referral pathways, tools and practices across Headquarters departments and Fields of Operation.</li><li>Assess institutional capacities, strengths, gaps and challenges related to: GBV prevention and risk mitigation; GBV prevention and response programming Safe identification and disclosure; Referral systems and service provision; Monitoring and information management; Accountability and coordination mechanisms.</li><li>Assess opportunities to strengthen harmonized GBV information management and reporting across programmes and Fields of Operation</li><li>Review existing partnerships relevant to GBV prevention and response.</li></ul><p>Deliverables: 1. Mapping of existing GBV policies, tools, services and referral pathways. 2. Institutional Capacity and Gap Assessment Report.</p><p>Deliverable 3: Stakeholder Consultations</p><ul><li>Facilitate consultations with Headquarters departments, programme areas and Field Offices.</li><li>Identify programme-specific roles, responsibilities and existing good practices and limitations.</li></ul><p>Deliverable: Synthesis and Design Report summarizing findings from the document review and stakeholder consultations, identifying key institutional strengths and gaps, findings, recommendations and presenting the proposed structure and strategic direction for the UNRWA Agency Framework for Multi-sectoral Prevention and Response to GBV.</p><p>Deliverable 4: Development of the GBV Framework</p><ul><li>Draft the UNRWA Agency Framework for Multi-sectoral Prevention and Response to GBV, including: Strategic outcomes including vision, objectives and guiding principles. Theory of Change. Governance and coordination arrangements. Programme-specific GBV commitments aligned with programs mandates. Roles and responsibilities of programs and operational actors. Operational standards for GBV prevention, risk mitigation, safe identification, referral and survivor-centered response. Institutional standards guiding GBV response. GBV risk identification and analysis approaches. Survivor-centred response principles. Referral pathways and coordination mechanisms. Monitoring, learning and accountability framework. Recommendations for implementation and institutionalization.</li></ul><p>Deliverable: First draft UNRWA agency framework for multi-sectoral prevention and response to GBV</p><p>Deliverable 5: Development of the GBV Programme Model</p><ul><li>Draft UNRWA GBV Prevention and Response Programme including: Core GBV prevention and response programme components Minimum list of service packages Suggested staffing profiles Community engagement approaches Prevention methodologies Response packages including suggested areas for expansion Monitoring framework including suggested outcome and output indicators Adaptation guidance for different humanitarian context</li></ul><p>Deliverable: First draft of UNRWA GBV Prevention and Response Programme model</p><p>Deliverable 6: Validation and Finalization</p><ul><li>Facilitate validation discussions with Headquarters and Field stakeholders.</li><li>Incorporate comments and recommendations.</li><li>Finalize the Framework and supporting tools.</li></ul><p>Deliverables: 1. Final UNRWA Agency Framework for Multi-sectoral Prevention and Response to GBV. 2. Implementation Roadmap. 3. UNRWA GBV prevention and response programme model</p><p>The consultant will be paid the lump sum of ($16,754.63), split into 3 instalments as described above upon satisfactory submission of the deliverables. Remuneration for this consultancy is on P4 level. The consultant will be remunerated based on the satisfactory deliverables of the agreed activities.</p><p><strong>Desired Candidate Profile</strong></p><ul><li>Advanced university degree in Gender Studies, Social Sciences, Human Rights, Protection, International Development, Public Policy or a related field.</li><li>At least 07 years of professional experience in GBV prevention and response, protection programming and institutional capacity strengthening.</li><li>Unless already serving as an international staff member in the UN Common System, at least two continuous years of relevant international experience outside UNRWA, and outside the country(s) of citizenship is required.</li><li>Demonstrated experience developing GBV strategies, frameworks, standards or operational guidance for UN agencies, NGOs or humanitarian organizations.</li><li>Strong knowledge of international standards and frameworks related to GBV, protection and gender equality.</li><li>Experience working in humanitarian or displacement contexts.</li><li>Proven experience facilitating multi-stakeholder consultations and institutional assessments.</li><li>Familiarity with UNRWA's operational context is highly desirable.</li><li>Excellent command of English; knowledge of Arabic is an asset.</li></ul>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>The project aims to strengthen the national TVET ecosystem, respond to labour market needs, and address youth unemployment and gender disparities. It supports the Ministry of Education's (MoE) ongoing TVET reforms as outlined in the Education Strategic Plan <strong>2020-2025</strong> and the recent BTEC based vocational education reform, offering Level 2 and 3 certifications across multiple specializations. The TA project is supporting MoE s TVET reforms through three key areas, namely: (i) strengthening key institutional and policy elements of the national skills ecosystem for a better enabling institutional and policy environment; (ii) enhancing skills development in priority sectors for young women and men through innovation in TVET; and (iii) improving the perception of TVET while advancing gender inclusivity and equity for all students to become a more attractive pathway for girls and boys in Jordan. Under Output 1.2.1, UNESCO is providing technical assistance to MoE to review and strengthen career guidance systems and tools in schools. This includes reviewing current systems and tools, enhancing the model for the provision of gender sensitive and inclusive career guidance, developing/adapting tools and resources, and training relevant personnel on the updated system, tools and resources. The Career Guidance Review, led by UNESCO with the support of the career guidance expert, assessed existing career guidance and counselling systems, tools and practices in Jordan s TVET sector and provided actionable recommendations for strengthening these services in alignment with national and international standards and priorities. Building on this work and following the development of the Career Guidance Model and Manual, there is a need to operationalize the model through a structured Training of Trainers (ToT) programme. This assignment is therefore not intended to create a new career guidance model. Rather, it will support MoE in institutionalizing and applying the developed Career Guidance Model and Manual through a practical ToT package and training process. The ToT will help build a core group of MoE trainers and relevant staff who can support consistent application of the manual in vocational education schools and contribute to future roll-out and scale up. This assignment falls under the Technical Assistance Programme implemented by UNESCO, which supports the delivery of Output 1.2.1: Technical assistance to MoE to review and strengthen career guidance systems and tools in schools. Specifically, the assignment contributes to Activity 1.2.1.4: Training of relevant personnel on the updated career guidance system, tools and resources, and supports Activity 1.2.1.5: Organising workshops and experience/information sharing sessions on the updated career guidance system for vocational education schools and gender responsive approaches in guidance processes for girls and boys. In line with this, UNESCO Amman Office seeks a qualified individual expert/consultant to design and deliver a ToT programme on the Career Guidance Model and Manual for selected MoE staff, supervisors, counsellors, and/or other relevant vocational education stakeholders. The consultant will ensure: • Development of a practical ToT design and training package aligned with the Career Guidance Model and Manual, MoE priorities, and the TVET reform context. • Delivery of a ToT that enables selected MoE participants to understand, facilitate, and support the use of the Career Guidance Model and Manual in vocational education schools. • Integration of gender-sensitive and inclusive career guidance approaches , labour market information, TVET/BTEC pathways, and links with work-based learning and employer engagement where relevant. • Documentation of training outcomes, participant feedback, lessons learned, and recommendations for future roll-out and scale up.&nbsp;</p><p><br></p><p><span >DUTIES/TASKS AND EXPECTED OUTPUT: The consultant will collaborate closely with the Ministry of Education and UNESCO s program team: To initiate efforts in this area, the expert/consultant will undertake the following tasks: 1. ToT Planning and Alignment Conduct consultations with UNESCO and relevant MoE counterparts to confirm the target participants, training objectives, delivery modality, duration, and expected post training application. The consultant will review the Career Guidance Model and Manual and translate its content into a practical ToT structure, ensuring alignment with MoE systems, existing counsellor roles, vocational education schools, and the broader TVET reform context. 2. Training of Trainers (ToT) Package Design and prepare a complete ToT package that enables selected participants to deliver or support future training and orientation sessions on the Career Guidance Model and Manual. The package should include, at minimum: • Training agenda and session plan. • PowerPoint slides and facilitator notes. • Participant handouts and practical exercises/case studies.</span></p><p>SKILLS AND COMPETENCIES • Strong understanding of labor market responsive programming, youth employability challenges, education-to-employment pathways, and inclusive/gender-sensitive career guidance approaches. • Strong coordination and follow up skills. • Demonstrated proficiency in MS Office applications and other relevant digital tools. • Strong organizational, planning, and prioritization skills. • Ability to manage multiple tasks and deadlines in a timely and efficient manner. • Ability to work proactively, with close daily coordination and limited supervision. • Ability to work effectively under pressure and in a multicultural environment. • High sense of professionalism, discretion, and reliability. • Excellent communication and interpersonal skills, including the ability to interact professionally and appropriately with government counterparts, education institutions, consultants, service providers, and other stakeholders. • Strong teamwork skills and ability to work constructively with UNESCO team members and external partners. • Good institutional understanding, including respect for communication channels, reporting lines, roles, responsibilities, and appropriate communication protocols. • Ability to maintain respectful, clear, and solution-oriented communication, including in sensitive or time sensitive situations. LANGUAGES • Excellent knowledge of English language including strong drafting, documentation, and reporting skills DESIRABLE QALIFICATIONS • Direct experience in Jordan and/or the MENA region, including familiarity with career guidance reforms, TVET/BTEC pathways, Ministry of Education systems, school counsellors, supervisors, or vocational education stakeholders. • Extensive experience in career services capacity building, especially in diverse contexts. • Track record of donor-funded education reform projects, preferably UNESCO.&nbsp;</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p><strong>REQUIRED QUALIFICATIONS</strong> EDUCATION • Advanced University degree (Master or equivalent) in education, international education, career development, counselling, psychology, organizational change, workforce development, TVET, education policy, social sciences, or a related field. WORK EXPERIENCE • At least 10years of relevant professional experience in career guidance/career development, employability, workforce education, TVET, or school to work transition programming. • Demonstrated experience designing and delivering training, ToT, workshops, or capacity-building programs for education personnel, career guidance practitioners, counsellors, career services staff, or similar stakeholders. • Proven experience developing user centered career guidance, career readiness, employability, or job-search manuals, toolkits, training materials, facilitator guides, digital resources, or practical implementation tools. • Proven Experience engaging with senior education stakeholders, universities, ministries, development partners, or education institutions on career guidance, career services, workforce development, or education reform initiatives. SKILLS AND COMPETENCIES • Strong understanding of labor market responsive programming, youth employability challenges, education-to-employment pathways, and inclusive/gender-sensitive career guidance approaches. • Strong coordination and follow up skills. • Demonstrated proficiency in MS Office applications and other relevant digital tools. • Strong organizational, planning, and prioritization skills. • Ability to manage multiple tasks and deadlines in a timely and efficient manner. • Ability to work proactively, with close daily coordination and limited supervision. • Ability to work effectively under pressure and in a multicultural environment. • High sense of professionalism, discretion, and reliability. • Excellent communication and interpersonal skills, including the ability to interact professionally and appropriately with government counterparts, education institutions, consultants, service providers, and other stakeholders. • Strong teamwork skills and ability to work constructively with UNESCO team members and external partners. • Good institutional understanding, including respect for communication channels, reporting lines, roles, responsibilities, and appropriate communication protocols. • Ability to maintain respectful, clear, and solution-oriented communication, including in sensitive or time sensitive situations. LANGUAGES • Excellent knowledge of English language including strong drafting, documentation, and reporting skills DESIRABLE QALIFICATIONS • Direct experience in Jordan and/or the MENA region, including familiarity with career guidance reforms, TVET/BTEC pathways, Ministry of Education systems, school counsellors, supervisors, or vocational education stakeholders. • Extensive experience in career services capacity building, especially in diverse contexts. • Track record of donor-funded education reform projects, preferably UNESCO. • Direct engagement with ministries and educational regulators across several countries. • Contextualized understanding of youth employability challenges and solutions in Jordan and MENA. • Expertise in building employer-education partnerships and designing work-based learning models for diverse populations. • Knowledge of the Arabic Language. • Experience in BTEC or any similar programs.</p><p></p></section>

<p><h4>Description</h4> <p>Robusta Technology Group (RTG) is a key driver of digital transformation by providing a holistic tech ecosystem. RTG works with its local and international partners to help build digital customer experiences, establish engineering hubs, and build ventures across multiple industries and domains. In this pursuit, RTG serves as a catalyst for impact and growth through events, spaces, and content focused on creating impact and growth across the different interactions.</p> <p>Octopus is proud to be part of the Robusta Technology Group (RTG), a leading tech consultancy group. With a decade of experience and a successful track record of delivering over 300 projects across Europe, the Middle East, and North America, RTG has established itself as a preferred employer in the Egyptian market. Octopus and Robusta are building a bridge between Europe and Africa, creating tailored hub solutions to connect companies with top talent across the globe.</p> <h4>Job overview</h4> <p>We are seeking an experienced senior Salesforce Agentforce to lead the design and delivery of enterprise-grade AI agent solutions using Salesforce Agentforce. This role requires deep expertise in Agentforce architecture, Salesforce Data Cloud (Data 360), Retrieval-Augmented Generation (RAG), and the Salesforce platform. You will work closely with business stakeholders, architects, delivery teams, and executive leadership to identify AI use cases, define solution architectures, and drive successful Agentforce implementations across complex enterprise environments.</p> <h4>Role responsibilities</h4> <ul> <li>Lead Agentforce discovery workshops to identify high-value AI use cases and assess solution fit.</li> <li>Define agent care plans, success metrics, adoption strategies, and implementation roadmaps.</li> <li>Architect Agentforce solutions, including:<br>   - Agents and sub-agents<br>   - Topics<br>   - Actions (Apex, Flow, Prompt-based, and Invocable Actions)<br>   - Instructions and orchestration</li> <li>Design grounding strategies using Salesforce Data Cloud (Data 360), Retrieval-Augmented Generation (RAG), vector databases, embedding and chunking techniques, and retrieval optimization for both structured and unstructured data.</li> <li>Design scalable Salesforce platform architectures, including:<br>   - Data model<br>   - Sharing and visibility model<br>   - Security architecture</li> <li>Develop solution extensions using Apex, Lightning Web Components (LWC), and Salesforce Flow.</li> <li>Produce technical architecture documentation, solution blueprints, and executive presentations.</li> <li>Establish architectural governance, implementation standards, and best practices to ensure scalability, reusability, and compliance with Agentforce platform guardrails.</li> <li>Collaborate with delivery teams, data engineers, integration architects, and enterprise stakeholders across multi-system environments, including ERP, CRM, middleware, and external AI services.</li> <li>Support pre-sales initiatives by contributing to solution design, effort estimation, demonstrations, and proof-of-concept (POC) development.</li> <li>Provide technical leadership and mentoring to project teams throughout the solution lifecycle.</li> </ul> <h4>Requirements</h4> <ul> <li>Proven experience delivering Salesforce Agentforce solutions in production environments or enterprise-scale proof of concepts.</li> <li>Strong understanding of Agentforce architecture, including:<br>   - Agents<br>   - Sub-agents<br>   - Topics<br>   - Actions<br>   - Instructions<br>   - Orchestration</li> <li>Experience facilitating AI use case discovery and designing agent care plans.</li> <li>Strong expertise in Salesforce Data Cloud (Data 360), including:<br>   - Data modelling<br>   - Batch and streaming ingestion<br>   - Data harmonisation<br>   - Identity resolution</li> <li>Deep understanding of Retrieval-Augmented Generation (RAG), including:<br>   - Vector databases<br>   - Embedding and chunking strategies<br>   - Retrieval optimisation<br>   - Grounding using Data Cloud and external knowledge sources</li> <li>Strong Salesforce platform architecture experience covering:<br>   - Data modelling<br>   - Security architecture<br>   - Sharing and visibility model (OWD, Roles, Sharing Rules)</li> <li>Advanced development skills in:<br>   - Apex<br>   - Lightning Web Components (LWC)<br>   - Salesforce Flow</li> <li>Experience designing enterprise integration patterns connecting Agentforce with external systems.</li> <li>Excellent stakeholder management and client-facing communication skills with the ability to present solutions to both technical and executive audiences.</li> <li>Understanding of the Agentforce consumption model.</li> <li>Experience with Agentforce Testing Center or equivalent AI testing frameworks.</li> </ul> <h4>Nice to have</h4> <ul> <li>Knowledge of Model Context Protocol (MCP).</li> <li>Experience with Agent-to-Agent (A2A) integration patterns.</li> <li>Experience designing headless Salesforce architectures.</li> <li>Agentblazer Legend status.</li> <li>Agentforce FDE Ready Practitioner accreditation.</li> </ul> <h4>Preferred Salesforce certifications</h4> <ul> <li>Salesforce Application Architect</li> <li>Salesforce Data Cloud Consultant</li> <li>Salesforce Agentforce Specialist</li> </ul> <h4>Benefits</h4> <ul> <li>Fully remote engagement.</li> <li>Opportunity to work on cutting-edge Salesforce AI and Agentforce implementations.</li> <li>Collaborate with leading enterprise clients on large-scale digital transformation programmes.</li> <li>Competitive contract rates and the opportunity to shape next-generation AI-powered customer experiences.</li> </ul></p><p></p>

<p><h4>Description</h4> <p>Robusta Technology Group (RTG) is a key driver of digital transformation by providing a holistic tech ecosystem. RTG works with its local and international partners to help build digital customer experiences, establish engineering hubs, and build ventures across multiple industries and domains. In this pursuit, RTG serves as a catalyst for impact and growth through events, spaces, and content focused on creating impact and growth across the different interactions.</p> <p>Octopus is proud to be part of the Robusta Technology Group (RTG), a leading tech consultancy group. With a decade of experience and a successful track record of delivering over 300 projects across Europe, the Middle East, and North America, RTG has established itself as a preferred employer in the Egyptian market. Octopus and Robusta are building a bridge between Europe and Africa, creating tailored hub solutions to connect companies with top talent across the globe.</p> <h4>Job overview</h4> <p>We are seeking an experienced senior Salesforce Agentforce to lead the design and delivery of enterprise-grade AI agent solutions using Salesforce Agentforce. This role requires deep expertise in Agentforce architecture, Salesforce Data Cloud (Data 360), Retrieval-Augmented Generation (RAG), and the Salesforce platform. You will work closely with business stakeholders, architects, delivery teams, and executive leadership to identify AI use cases, define solution architectures, and drive successful Agentforce implementations across complex enterprise environments.</p> <h4>Role responsibilities</h4> <ul> <li>Lead Agentforce discovery workshops to identify high-value AI use cases and assess solution fit.</li> <li>Define agent care plans, success metrics, adoption strategies, and implementation roadmaps.</li> <li>Architect Agentforce solutions, including:<br>   - Agents and sub-agents<br>   - Topics<br>   - Actions (Apex, Flow, Prompt-based, and Invocable Actions)<br>   - Instructions and orchestration</li> <li>Design grounding strategies using Salesforce Data Cloud (Data 360), Retrieval-Augmented Generation (RAG), vector databases, embedding and chunking techniques, and retrieval optimization for both structured and unstructured data.</li> <li>Design scalable Salesforce platform architectures, including:<br>   - Data model<br>   - Sharing and visibility model<br>   - Security architecture</li> <li>Develop solution extensions using Apex, Lightning Web Components (LWC), and Salesforce Flow.</li> <li>Produce technical architecture documentation, solution blueprints, and executive presentations.</li> <li>Establish architectural governance, implementation standards, and best practices to ensure scalability, reusability, and compliance with Agentforce platform guardrails.</li> <li>Collaborate with delivery teams, data engineers, integration architects, and enterprise stakeholders across multi-system environments, including ERP, CRM, middleware, and external AI services.</li> <li>Support pre-sales initiatives by contributing to solution design, effort estimation, demonstrations, and proof-of-concept (POC) development.</li> <li>Provide technical leadership and mentoring to project teams throughout the solution lifecycle.</li> </ul> <h4>Requirements</h4> <ul> <li>Proven experience delivering Salesforce Agentforce solutions in production environments or enterprise-scale proof of concepts.</li> <li>Strong understanding of Agentforce architecture, including:<br>   - Agents<br>   - Sub-agents<br>   - Topics<br>   - Actions<br>   - Instructions<br>   - Orchestration</li> <li>Experience facilitating AI use case discovery and designing agent care plans.</li> <li>Strong expertise in Salesforce Data Cloud (Data 360), including:<br>   - Data modelling<br>   - Batch and streaming ingestion<br>   - Data harmonisation<br>   - Identity resolution</li> <li>Deep understanding of Retrieval-Augmented Generation (RAG), including:<br>   - Vector databases<br>   - Embedding and chunking strategies<br>   - Retrieval optimisation<br>   - Grounding using Data Cloud and external knowledge sources</li> <li>Strong Salesforce platform architecture experience covering:<br>   - Data modelling<br>   - Security architecture<br>   - Sharing and visibility model (OWD, Roles, Sharing Rules)</li> <li>Advanced development skills in:<br>   - Apex<br>   - Lightning Web Components (LWC)<br>   - Salesforce Flow</li> <li>Experience designing enterprise integration patterns connecting Agentforce with external systems.</li> <li>Excellent stakeholder management and client-facing communication skills with the ability to present solutions to both technical and executive audiences.</li> <li>Understanding of the Agentforce consumption model.</li> <li>Experience with Agentforce Testing Center or equivalent AI testing frameworks.</li> </ul> <h4>Nice to have</h4> <ul> <li>Knowledge of Model Context Protocol (MCP).</li> <li>Experience with Agent-to-Agent (A2A) integration patterns.</li> <li>Experience designing headless Salesforce architectures.</li> <li>Agentblazer Legend status.</li> <li>Agentforce FDE Ready Practitioner accreditation.</li> </ul> <h4>Preferred Salesforce certifications</h4> <ul> <li>Salesforce Application Architect</li> <li>Salesforce Data Cloud Consultant</li> <li>Salesforce Agentforce Specialist</li> </ul> <h4>Benefits</h4> <ul> <li>Fully remote engagement.</li> <li>Opportunity to work on cutting-edge Salesforce AI and Agentforce implementations.</li> <li>Collaborate with leading enterprise clients on large-scale digital transformation programmes.</li> <li>Competitive contract rates and the opportunity to shape next-generation AI-powered customer experiences.</li> </ul></p><p></p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Robusta Technology Group (RTG) is a key driver of digital transformation by providing a holistic tech ecosystem.<br> RTG works with its local and international partners to help build digital customer experiences, establish engineering hubs and build ventures across multiple industries and domains.<br> In this pursuit, RTG serves as a catalyst for impact and growth through events, spaces and content focused on creating impact and growth across the different interactions.<br> Octopus is proud to be part of the Robusta Technology Group (RTG), a leading tech consultancy group.<br> With a decade of experience and a successful track record of delivering over 300 projects across Europe, the Middle East, and North America, RTG has established itself as a preferred employer in the Egyptian market.<br> Octopus and Robusta are building a bridge between Europe and Africa, creating tailored hub solutions to connect companies with top talent across the globe.<br> Job Overview We are seeking an experienced Senior Salesforce Agentforce to lead the design and delivery of enterprise-grade AI agent solutions using Salesforce Agentforce.<br> This role requires deep expertise in Agentforce architecture, Salesforce Data Cloud (Data 360), Retrieval-Augmented Generation (RAG), and the Salesforce platform.<br> You will work closely with business stakeholders, architects, delivery teams, and executive leadership to identify AI use cases, define solution architectures, and drive successful Agentforce implementations across complex enterprise environments.<br> Role Responsibilities Lead Agentforce discovery workshops to identify high-value AI use cases and assess solution fit.<br> Define agent care plans, success metrics, adoption strategies, and implementation roadmaps.<br> Architect Agentforce solutions, including: - Agents and sub-agents - Topics - Actions (Apex, Flow, Prompt-based, and Invocable Actions) - Instructions and orchestration Design grounding strategies using Salesforce Data Cloud (Data 360), Retrieval-Augmented Generation (RAG), vector databases, embedding and chunking techniques, and retrieval optimization for both structured and unstructured data.<br> Design scalable Salesforce platform architectures, including: - Data model - Sharing and visibility model - Security architecture Develop solution extensions using Apex, Lightning Web Components (LWC), and Salesforce Flow.<br> Produce technical architecture documentation, solution blueprints, and executive presentations.<br> Establish architectural governance, implementation standards, and best practices to ensure scalability, reusability, and compliance with Agentforce platform guardrails.<br> Collaborate with delivery teams, data engineers, integration architects, and enterprise stakeholders across multi-system environments, including ERP, CRM, middleware, and external AI services.<br> Support pre-sales initiatives by contributing to solution design, effort estimation, demonstrations, and proof-of-concept (POC) development.<br> Provide technical leadership and mentoring to project teams throughout the solution lifecycle.<br> Fully remote engagement.<br> Opportunity to work on cutting-edge Salesforce AI and Agentforce implementations.<br> Collaborate with leading enterprise clients on large-scale digital transformation programmes.<br> Competitive contract rates and the opportunity to shape next-generation AI-powered customer experiences.<br> Proven experience delivering Salesforce Agentforce solutions in production environments or enterprise-scale proof of concepts.<br> Strong understanding of Agentforce architecture, including: Agents Sub-agents Topics Actions Instructions Orchestration Experience facilitating AI use case discovery and designing agent care plans.<br> Strong expertise in Salesforce Data Cloud (Data 360), including: Data modelling Batch and streaming ingestion Data harmonisation Identity resolution Deep understanding of Retrieval-Augmented Generation (RAG), including: Vector databases Embedding and chunking strategies Retrieval optimisation Grounding using Data Cloud and external knowledge sources Strong Salesforce platform architecture experience covering: Data modelling Security architecture Sharing and visibility model (OWD, Roles, Sharing Rules) Advanced development skills in: Apex Lightning Web Components (LWC) Salesforce Flow Experience designing enterprise integration patterns connecting Agentforce with external systems.<br> Excellent stakeholder management and client-facing communication skills with the ability to present solutions to both technical and executive audiences.<br> Understanding of the Agentforce consumption model.<br> Experience with Agentforce Testing Center or equivalent AI testing frameworks.<br> Nice to Have Knowledge of Model Context Protocol (MCP).<br> Experience with Agent-to-Agent (A2A) integration patterns.<br> Experience designing headless Salesforce architectures.<br> Agentblazer Legend status.<br> Agentforce FDE Ready Practitioner accreditation.<br> Preferred Salesforce Certifications Salesforce Application Architect Salesforce Data Cloud Consultant Salesforce Agentforce Specialist</span> </div>

<p><h4>Description</h4> <p>We're looking for an experienced senior data scientist to design and deliver data-driven solutions that solve complex business problems and create measurable impact.</p> <p>Working closely with business stakeholders, product teams, and technical experts, you'll transform business challenges into scalable analytical, machine learning, and GenAI solutions. From defining use cases to deploying production-ready models, you'll play a key role in delivering innovative AI solutions that drive better decision-making and customer outcomes.</p> <h4>Requirements</h4> <h4>What you'll do</h4> <ul> <li>Collaborate with business stakeholders to identify and prioritize AI and analytics opportunities</li> <li>Translate business requirements into scalable data science and machine learning solutions</li> <li>Validate data availability and define analytical approaches for new use cases</li> <li>Build predictive models, machine learning solutions, and GenAI applications</li> <li>Design robust data pipelines and analytical workflows</li> <li>Apply data processing, feature engineering, and statistical modelling techniques</li> <li>Ensure solutions are scalable, production-ready, and aligned with software engineering and MLOps best practices</li> <li>Present analytical findings and recommendations to technical and executive stakeholders</li> <li>Communicate AI capabilities, feasibility, risks, and expected business value in a clear and practical way</li> <li>Mentor junior team members and support technical delivery across multiple initiatives</li> </ul> <h4>You're our match if you have</h4> <ul> <li>Master's degree in data science, computer science, artificial intelligence, mathematics, software engineering, or a related field</li> <li>5+ years of hands-on experience delivering data science or machine learning solutions</li> <li>Strong Python programming skills and experience with modern data science libraries</li> <li>Experience building predictive models, machine learning solutions, and GenAI applications</li> <li>Strong understanding of statistics, data modelling, and feature engineering</li> <li>Experience designing scalable data pipelines and production-ready AI solutions</li> <li>Familiarity with MLOps, model deployment, and machine learning lifecycle management</li> <li>Excellent stakeholder management and communication skills</li> <li>Ability to translate complex technical concepts into business value</li> </ul> <h4>Bonus points if you have experience with</h4> <ul> <li>Telecommunications or other customer-centric industries</li> <li>Large-scale customer analytics and segmentation</li> <li>Large language models (LLMs) and retrieval-augmented generation (RAG)</li> <li>Cloud platforms such as Azure, AWS, or Google Cloud</li> <li>Databricks, Spark, or distributed data processing</li> <li>Docker, Kubernetes, or CI/CD pipelines</li> <li>Leading or mentoring technical teams</li> </ul></p><p></p>

<p><h4>Description</h4> <p>We're looking for an experienced senior data scientist to design and deliver data-driven solutions that solve complex business problems and create measurable impact.</p> <p>Working closely with business stakeholders, product teams, and technical experts, you'll transform business challenges into scalable analytical, machine learning, and GenAI solutions. From defining use cases to deploying production-ready models, you'll play a key role in delivering innovative AI solutions that drive better decision-making and customer outcomes.</p> <h4>Requirements</h4> <h4>What you'll do</h4> <ul> <li>Collaborate with business stakeholders to identify and prioritize AI and analytics opportunities</li> <li>Translate business requirements into scalable data science and machine learning solutions</li> <li>Validate data availability and define analytical approaches for new use cases</li> <li>Build predictive models, machine learning solutions, and GenAI applications</li> <li>Design robust data pipelines and analytical workflows</li> <li>Apply data processing, feature engineering, and statistical modelling techniques</li> <li>Ensure solutions are scalable, production-ready, and aligned with software engineering and MLOps best practices</li> <li>Present analytical findings and recommendations to technical and executive stakeholders</li> <li>Communicate AI capabilities, feasibility, risks, and expected business value in a clear and practical way</li> <li>Mentor junior team members and support technical delivery across multiple initiatives</li> </ul> <h4>You're our match if you have</h4> <ul> <li>Master's degree in data science, computer science, artificial intelligence, mathematics, software engineering, or a related field</li> <li>5+ years of hands-on experience delivering data science or machine learning solutions</li> <li>Strong Python programming skills and experience with modern data science libraries</li> <li>Experience building predictive models, machine learning solutions, and GenAI applications</li> <li>Strong understanding of statistics, data modelling, and feature engineering</li> <li>Experience designing scalable data pipelines and production-ready AI solutions</li> <li>Familiarity with MLOps, model deployment, and machine learning lifecycle management</li> <li>Excellent stakeholder management and communication skills</li> <li>Ability to translate complex technical concepts into business value</li> </ul> <h4>Bonus points if you have experience with</h4> <ul> <li>Telecommunications or other customer-centric industries</li> <li>Large-scale customer analytics and segmentation</li> <li>Large language models (LLMs) and retrieval-augmented generation (RAG)</li> <li>Cloud platforms such as Azure, AWS, or Google Cloud</li> <li>Databricks, Spark, or distributed data processing</li> <li>Docker, Kubernetes, or CI/CD pipelines</li> <li>Leading or mentoring technical teams</li> </ul></p><p></p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your CV in English and indicate your level of English proficiency.<br> Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.<br> Participation is project-based, not permanent employment.<br> What this opportunity involves We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<br> You'll create challenging tasks and evaluation criteria within realistic simulated environments: Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history Design tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agent Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust What this is NOT Not data labeling Not prompt engineering Not writing code from scratch - the agent writes most of the code; you guide and evaluate What we look for 5+ years in software development Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis Experience writing tests (functional, integration) English proficiency - B2+ Why this is hard Frontier models are already good at coding.<br> Creating a task that genuinely challenges the best models is non-trivial.<br> You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution.<br> Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<br> How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Effort estimate Tasks for this project are estimated to take 20 hours to complete, depending on complexity.<br> This is an estimate and not a schedule requirement; you choose when and how to work.<br> Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<br> Compensation Up to $50/hr equivalent , depending on level and pace.<br> Tasks are estimated at ~20 hours each; you set your own schedule.<br></span> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> Brand Manager (Fashion Retail) <ul> <li><span>Posting Date</span>: 20/09/2026</li> <li><span>Ref</span>: SJOR-154</li> <li><span>Position</span>: Brand Manager (Fashion Retail)</li> <li> </li><li><span>Location</span>: Jordan</li> <li><span>City</span>: Amman </li> <li> </li><li><span>Sector</span>: Retail</li> <li><span>Years of Experience</span> 8+ years of experience </li> <li> </li><li><span>Qualification</span>: Bachelor’s degree in Business, Retail Management, Fashion Merchandising, or a related field (MBA is an advantage)</li> <li><span>Salary</span>: Up to 1800 JOD Basic Salary</li> <li><span>Workdays</span>: 5</li> <li> </li><li><span>Description</span>: Our client is a prominent, large-scale multi-brand retail and franchise operating group based in Amman, Jordan. The company is seeking an experienced, analytical, and results-driven Brand Manager to lead overall commercial performance, seasonal product buying, inventory productivity, pricing recommendations, and franchisor/principal relationships across its brand portfolio. The role reports directly to the Commercial Director and will work closely as a peer to the Marketing Manager. Key focus areas include: <ul> <li>Driving commercial performance, sales targets, and profitability across assigned brands.</li> <li>Managing seasonal product buying, assortment planning, and Open-to-Buy (OTB) allocations.</li> <li>Optimizing inventory cover, replenishment, and markdown strategies.</li> <li>Managing and strengthening relationships with international brand principals and franchisors.</li> <li>Aligning with cross-functional teams (Marketing, Operations, and Finance) to execute commercial goals.</li> </ul> Key Responsibilities Commercial Strategy &amp; Buying <ul> <li>Own seasonal buying and assortment planning for assigned brand(s), aligning with franchisor collections and market positioning.</li> <li>Negotiate buying terms, minimum order quantities (MOQs), and seasonal purchase plans within delegated authority.</li> <li>Protect brand positioning by keeping range depth, price points, and promotional activity aligned with franchise standards.</li> </ul> Inventory Productivity &amp; Allocation <ul> <li>Oversee replenishment priorities, stock allocation, and inter-store transfer decisions.</li> <li>Monitor size availability, stock cover, sell-through rates, and stock ageing to minimize slow-moving inventory.</li> <li>Direct support teams (Buying Coordinators &amp; Allocation Analysts) to ensure smooth stock flow and data management.</li> </ul> Pricing &amp; Markdown Management <ul> <li>Recommend retail prices, product bundles, and promotional markdowns based on pricing policies and market trends.</li> <li>Manage and approve in-season markdowns within authorized budgets.</li> <li>Ensure accurate price and promotion execution across physical stores and online channels.</li> </ul> Franchisor &amp; Vendor Relationship Management <ul> <li>Serve as the primary point of contact for brand principals regarding orders, shipments, product data, and trading results.</li> <li>Manage co-op marketing budgets and ensure full compliance with international brand standards.</li> <li>Prepare and submit regular monthly performance and trading reports to brand principals.</li> </ul> Team Leadership &amp; Performance Management <ul> <li>Guide and evaluate direct reports (Buying Coordinator &amp; Merchandising Analyst).</li> <li>Partner with the Marketing Manager on launch dates, co-op funds, and visual merchandising standards.</li> <li>Coordinate with Area and Store Managers on store demand, space allocation, and stock feedback.</li> <li>Track sales KPIs, sell-through rates, and present monthly brand performance dashboards to senior executive management.</li> </ul> Key Qualifications <ul> <li>Minimum 6–8+ years of progressive brand management, buying, or merchandising experience within multi-brand retail or franchise operations.</li> <li>Strong preference for candidates with experience in the GCC market.</li> <li>Bachelor’s degree in Business Administration, Retail Management, Fashion Merchandising, or a related commercial discipline (MBA is an advantage).</li> <li>Strong expertise in: <ul> <li>Open-to-Buy (OTB) planning, allocation, and replenishment systems.</li> <li>Markdown management and inventory productivity (stock cover/sell-through).</li> <li>Franchisor negotiation and brand standard compliance.</li> <li>Retail analytics and advanced MS Excel/ERP systems.</li> </ul> </li> <li>Native-level Arabic and fluent English language skills are mandatory.</li> <li>Based in or willing to relocate to Amman, Jordan (open to candidates inside Jordan or returning from the GCC region).</li> </ul> <br> More<br> </li> </ul> <br> <br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your CV in English and indicate your level of English proficiency.<br> Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.<br> Participation is project-based, not permanent employment.<br> What this opportunity involves We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<br> You'll create challenging tasks and evaluation criteria within realistic simulated environments: Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history Design tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agent Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust What this is NOT Not data labeling Not prompt engineering Not writing code from scratch - the agent writes most of the code; you guide and evaluate What we look for 5+ years in software development Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis Experience writing tests (functional, integration) English proficiency - B2+ Why this is hard Frontier models are already good at coding.<br> Creating a task that genuinely challenges the best models is non-trivial.<br> You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution.<br> Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<br> How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Compensation Up to $40/hr equivalent , depending on level and pace.<br> Tasks are estimated at ~20 hours each; you set your own schedule.<br></span> </div>

<p><br></p><p><b>What you'll be doing</b></p><ul><li>Build and maintain Supplier/Retailer relationships in order to build a strong working relationship</li><li>Cascade targets to Sales Team Leads</li><li>Handle and respond to existing products queries from clients quickly, effectively and accurately</li><li>Provide customers with the appropriate selection, sampling of products in response of their inquiries and provide quotations accordingly</li><li>Anticipate the clients needs and provide appropriate solutions to meet these needs</li><li>Facilitate prospecting of new clients to identify and develop new accounts</li><li>Introduce the company s profile and communicate the selection of products available</li><li>Support in increasing the sales and following up on orders, stock and deliveries</li><li>Oversee collection of receivables in timely fashion</li><li>Provide market feedback to the commercial team regarding movement of goods / brands</li><li>Coordinate with the marketing team on the budget requirements and limits</li><li>Coordinate with sales team to ensure quality and accuracy of merchandising</li><li>Keep abreast the market conditions and trends in the field pertinent to brands / products</li><li>Support the team with New Product Launch strategy and information</li><li>Liaise with Rewards and People Partner to design updated commission schemes</li><li>Participate in relevant projects and community activities as and when needed</li><li>Develop and motivate team members to ensure transfer of know-how and continuous positive work environment</li><li>Assign individual objectives for employee performance management purposes, manage performance, empower team, and provide formal and informal feedback in order to support professional development and maximize performance</li></ul><p><b><br></b></p><p><b>What you'll need to succeed</b></p><ul><li>Minimum 8years of relevant experience within the realm of luxury fashion brands</li><li>Proficiency in English with fluency in Arabic</li><li>Strong leadership capabilities</li><li>An intuitive ability to anticipate and address customer needs</li><li>Proactive monitoring of industry trends and competition to uphold optimal customer satisfaction levels</li><li>Willingness to adapt work methods for enhanced performance.</li></ul><p>What we can offer you</p><p>With us, you will turn your aspirations into reality. We will help shape your journey through enriching experiences, learning and development opportunities and exposure to different assignments within your role or through internal mobility. Our Group offers diverse career paths for those who are extraordinary, every day. We recognise the value that you bring, and we strive to provide a competitive benefits package which includes health care, child education contribution, remote and flexible working policies as well as exclusive employee discounts.</p><p><br></p><p><strong>Desired Candidate Profile</strong></p><ul><li>Minimum 8years of relevant experience within the realm of luxury fashion brands</li><li>Proficiency in English with fluency in Arabic</li><li>Strong leadership capabilities</li><li>An intuitive ability to anticipate and address customer needs</li><li>Proactive monitoring of industry trends and competition to uphold optimal customer satisfaction levels</li><li>Willingness to adapt work methods for enhanced performance.</li></ul>

<p><h4>Description</h4> <p>The data cleansing program director leads the government-wide data cleansing program — driving large-scale data quality uplift across multiple government entities. You will own the cleansing strategy, orchestrate a multi-vendor delivery model, oversee enterprise data modelling, and ensure that cleansed datasets are published into the government-wide catalogue and sharing platforms — sustainably, with strong governance, ongoing monitoring, and continuous improvement.</p> <ul> <li><strong>Define and lead the government-wide data cleansing strategy</strong> aligned with data quality standards, policies, and government priorities.</li> <li><strong>Establish a structured framework</strong> to prioritize critical datasets and drive phased execution across entities.</li> <li><strong>Standardize, automate, and scale the end-to-end data cleansing lifecycle</strong> — leveraging advanced tools and AI-driven solutions; govern reusable accelerators.</li> <li><strong>Establish and oversee a multi-vendor delivery model</strong> — coordinated execution, performance management, and scalability across entities.</li> <li><strong>Oversee large-scale data quality improvement initiatives</strong> aligned to defined quality dimensions, rules, and thresholds.</li> <li><strong>Oversee development of entities' enterprise data models</strong> — aligned with government-wide data standards, central information models, and interoperability requirements.</li> <li><strong>Ensure creation, standardization, and publication of cleansed datasets</strong> into the government-wide data catalogue and sharing platforms — enabling accessibility and reuse.</li> <li><strong>Oversee development of data quality dashboards</strong> to track KPIs and cleansing progress.</li> <li><strong>Establish and lead program governance bodies</strong> — driving timely, quality delivery, issue resolution, and stakeholder alignment.</li> <li><strong>Establish and govern sustainable data quality and cleansing frameworks</strong> for long-term maintenance and continuous improvement.</li> <li><strong>Provide regular reporting to senior leadership</strong> on program progress, risks, and impact on data maturity and value realization.</li> </ul> <h4>Requirements</h4> <ul> <li>Bachelor's or master's in data management, IT, engineering, or related field.</li> <li>20+ years in data management, data quality, or large-scale transformation programs (preferably with exposure in Europe or North America).</li> <li>Proven track record leading enterprise-wide or national data cleansing / data quality initiatives, including multi-vendor delivery models.</li> <li>Strong expertise in data quality frameworks, profiling, and remediation techniques.</li> <li>Familiarity with modern data platforms — Informatica, Azure, Databricks, Snowflake, or similar.</li> <li>Demonstrated experience managing large vendor ecosystems and complex multi-stakeholder programs.</li> <li>Strong leadership and stakeholder management skills at senior government or enterprise level.</li> <li>Excellent English communication; Arabic a plus.</li> </ul></p><p></p>