Python Developer Jobs in Jordan

<p><h4>Description</h4> <p><strong>Job purpose</strong><br> As the team lead at Tarjama, you will be responsible for leading a technical team in the design, development, and delivery of high-quality technology solutions aligned with Tarjama’s strategic goals. This role ensures the successful execution of engineering tasks, enforces development best practices, and acts as a hands-on contributor while also coordinating with cross-functional teams. The team lead mentors team members and ensures the timely delivery of projects. They also translate technical direction into day-to-day implementation.</p> <h4>Duties & responsibilities</h4> <h4>Technical leadership & execution oversight</h4> <ul> <li>Oversee daily development activities, ensuring alignment with coding standards, architecture guidelines, and delivery timelines.</li> <li>Guide system design and architecture discussions, providing hands-on technical input where needed.</li> <li>Support engineers in problem-solving, debugging, and performance optimization, acting as a key technical escalation point.</li> <li>Review and approve key code components, ensuring quality, scalability, and maintainability.</li> </ul> <h4>Team management & mentorship</h4> <ul> <li>Lead, coach, and develop a team of engineers with varying levels of experience.</li> <li>Conduct regular 1:1s, performance check-ins, and technical feedback sessions to ensure growth and accountability.</li> <li>Facilitate onboarding and continuous technical upskilling of team members.</li> <li>Foster a culture of knowledge sharing, collaboration, and continuous improvement.</li> </ul> <h4>Collaboration & cross-functional alignment</h4> <ul> <li>Work closely with product, QA, DevOps, and design teams to ensure shared understanding of project goals and priorities.</li> <li>Help translate product requirements into actionable development plans and ensure clear task delegation.</li> <li>Act as a liaison between the development team and technology leadership, providing visibility into progress, risks, and resource needs.</li> </ul> <h4>Code quality, documentation & standards</h4> <ul> <li>Enforce best practices in coding, documentation, testing, and deployment.</li> <li>Promote peer code reviews, unit testing, and automation to ensure reliability and consistency.</li> <li>Ensure comprehensive documentation is maintained for all critical systems and architectural decisions.</li> <li>Support continuous improvement of internal development workflows and tools.</li> </ul> <h4>System support & deployment coordination</h4> <ul> <li>Collaborate with DevOps and infrastructure teams to ensure system performance, CI/CD readiness, and release reliability.</li> <li>Monitor deployment readiness and troubleshoot issues during staging and production releases.</li> <li>Participate in the evaluation and adoption of new technologies and frameworks that align with business needs.</li> </ul> <h4>Education, experience & qualifications</h4> <ul> <li>Bachelor’s degree in computer science, software engineering, or a related field.</li> <li>8+ years of hands-on software development experience with at least 2 years in a technical leadership or team lead role.</li> <li>Strong experience with Node.js; Python is a plus.</li> <li>Proficiency in designing and reviewing scalable architectures using microservices and RESTful APIs.</li> <li>Experience working with relational and non-relational databases (e.g., MySQL, PostgreSQL, MongoDB, Redis).</li> <li>Solid experience in Agile/Scrum environments and sprint management.</li> <li>Proficient in English language.</li> </ul> <h4>Behavioral competencies</h4> <ul> <li>Communication</li> <li>Decision making</li> <li>Stakeholder management</li> <li>Team building & management</li> <li>Conflict management</li> <li>Results orientation</li> <li>Influencing others</li> </ul> <h4>Technical competencies</h4> <ul> <li>Backend development (Node.js, Python is a plus)</li> <li>Microservices & system architecture</li> <li>RESTful API design & integration</li> <li>Code review & quality standards</li> <li>Cloud infrastructure (AWS, Azure)</li> <li>CI/CD & DevOps collaboration</li> <li>Database design & optimization</li> <li>Performance monitoring & debugging</li> <li>Documentation & technical writing</li> <li>Agile development practices</li> </ul></p><p></p>

<p><h4>Description</h4> <p><strong>Job purpose</strong><br> As the team lead at Tarjama, you will be responsible for leading a technical team in the design, development, and delivery of high-quality technology solutions aligned with Tarjama’s strategic goals. This role ensures the successful execution of engineering tasks, enforces development best practices, and acts as a hands-on contributor while also coordinating with cross-functional teams. The team lead mentors team members and ensures the timely delivery of projects. They also translate technical direction into day-to-day implementation.</p> <h4>Duties & responsibilities</h4> <h4>Technical leadership & execution oversight</h4> <ul> <li>Oversee daily development activities, ensuring alignment with coding standards, architecture guidelines, and delivery timelines.</li> <li>Guide system design and architecture discussions, providing hands-on technical input where needed.</li> <li>Support engineers in problem-solving, debugging, and performance optimization, acting as a key technical escalation point.</li> <li>Review and approve key code components, ensuring quality, scalability, and maintainability.</li> </ul> <h4>Team management & mentorship</h4> <ul> <li>Lead, coach, and develop a team of engineers with varying levels of experience.</li> <li>Conduct regular 1:1s, performance check-ins, and technical feedback sessions to ensure growth and accountability.</li> <li>Facilitate onboarding and continuous technical upskilling of team members.</li> <li>Foster a culture of knowledge sharing, collaboration, and continuous improvement.</li> </ul> <h4>Collaboration & cross-functional alignment</h4> <ul> <li>Work closely with product, QA, DevOps, and design teams to ensure shared understanding of project goals and priorities.</li> <li>Help translate product requirements into actionable development plans and ensure clear task delegation.</li> <li>Act as a liaison between the development team and technology leadership, providing visibility into progress, risks, and resource needs.</li> </ul> <h4>Code quality, documentation & standards</h4> <ul> <li>Enforce best practices in coding, documentation, testing, and deployment.</li> <li>Promote peer code reviews, unit testing, and automation to ensure reliability and consistency.</li> <li>Ensure comprehensive documentation is maintained for all critical systems and architectural decisions.</li> <li>Support continuous improvement of internal development workflows and tools.</li> </ul> <h4>System support & deployment coordination</h4> <ul> <li>Collaborate with DevOps and infrastructure teams to ensure system performance, CI/CD readiness, and release reliability.</li> <li>Monitor deployment readiness and troubleshoot issues during staging and production releases.</li> <li>Participate in the evaluation and adoption of new technologies and frameworks that align with business needs.</li> </ul> <h4>Education, experience & qualifications</h4> <ul> <li>Bachelor’s degree in computer science, software engineering, or a related field.</li> <li>8+ years of hands-on software development experience with at least 2 years in a technical leadership or team lead role.</li> <li>Strong experience with Node.js; Python is a plus.</li> <li>Proficiency in designing and reviewing scalable architectures using microservices and RESTful APIs.</li> <li>Experience working with relational and non-relational databases (e.g., MySQL, PostgreSQL, MongoDB, Redis).</li> <li>Solid experience in Agile/Scrum environments and sprint management.</li> <li>Proficient in English language.</li> </ul> <h4>Behavioral competencies</h4> <ul> <li>Communication</li> <li>Decision making</li> <li>Stakeholder management</li> <li>Team building & management</li> <li>Conflict management</li> <li>Results orientation</li> <li>Influencing others</li> </ul> <h4>Technical competencies</h4> <ul> <li>Backend development (Node.js, Python is a plus)</li> <li>Microservices & system architecture</li> <li>RESTful API design & integration</li> <li>Code review & quality standards</li> <li>Cloud infrastructure (AWS, Azure)</li> <li>CI/CD & DevOps collaboration</li> <li>Database design & optimization</li> <li>Performance monitoring & debugging</li> <li>Documentation & technical writing</li> <li>Agile development practices</li> </ul></p><p></p>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>Manage and maintain cloud and on-premises infrastructure across development, staging, and production environments. Build, optimize, and support CI/CD pipelines to improve deployment efficiency and reliability. Administer Linux servers, web servers (Nginx/Apache), and containerized environments. Implement security best practices, server hardening, access controls, and infrastructure monitoring. Monitor system performance, availability, logs, and network activity to ensure operational stability. Troubleshoot production issues and support incident response and recovery activities. Manage backups, disaster recovery procedures, and infrastructure documentation. Support database operations, queue workers, scheduled jobs, Redis, and background services. Collaborate with development and QA teams to ensure smooth and secure software releases. Optimize infrastructure performance, scalability, and cloud resource utilization. Participate in on-call support for critical production and infrastructure incidents when required.</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a related field.</li><li>4+ years of experience in DevOps, Cloud Engineering, System Administration, or a similar role.</li><li>Strong experience with Linux administration and managing production environments.</li><li>Hands-on experience with cloud platforms, preferably Google Cloud Platform (GCP).</li><li>Experience with CI/CD tools such as GitHub Actions, GitLab CI/CD, Jenkins, or similar.</li><li>Strong knowledge of Docker, Nginx/Apache, networking, and infrastructure security.</li><li>Experience with monitoring, logging, automation, and scripting tools (Bash, Python, or similar).</li><li>Familiarity with MySQL, Redis, cron jobs, queue management, and backup/recovery processes.</li><li>Strong troubleshooting, documentation, and communication skills.</li><li>Experience with Kubernetes, Terraform, Ansible, Grafana, Prometheus, Laravel/PHP, or Cloudflare is an advantage.</li></ul><p></p></section>

<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>

<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><h4>Description</h4> <p>BlackStone eIT is actively looking for a dedicated AI team lead to spearhead our artificial intelligence initiatives. This role involves leading a talented team of AI professionals to create innovative AI-driven solutions that align with the company's vision. You will play a crucial part in strategizing, developing, and deploying AI technologies that enhance our products and services while maintaining the highest standards of excellence.</p> <h4>Responsibilities:</h4> <ul> <li>Lead the AI team in designing, developing, and implementing AI models and systems.</li> <li>Collaborate with stakeholders to identify AI opportunities that drive business value.</li> <li>Guide the team to effectively use machine learning frameworks and tools.</li> <li>Oversee project lifecycle from research and prototyping to production deployment.</li> <li>Maintain knowledge of latest trends and advancements in AI and machine learning.</li> <li>Establish best practices and foster a culture of continuous improvement and innovation.</li> </ul> <h4>Requirements</h4> <ul> <li>Experience: 6+ years of hands-on experience in machine learning, deep learning, or AI engineering.</li> <li>3+ years of experience in a technical leadership or mentoring role.</li> <li>Programming & frameworks: Expert-level proficiency in Python and deep learning frameworks (PyTorch is strongly preferred, or TensorFlow).</li> <li>Cloud infrastructure: Extensive, hands-on experience with Microsoft Azure, specifically building training and deployment pipelines using Azure ML workspace, MLflow, and container orchestration (Docker/Kubernetes).</li> <li>NLP expertise: Deep understanding of modern NLP architectures (Transformers, BERT, GPT variants), tokenization, vector databases, and libraries like Hugging Face and LangChain/Lang Graph.</li> <li>CV expertise: Strong mathematical foundation in image processing and experience building custom models using OpenCV, YOLO architectures, and PyTorch Vision.</li> <li>MLOps: Proven ability to build CI/CD pipelines for machine learning models, manage model registries, and monitor model drift in production.</li> <li>Experience with building and deploying autonomous AI agents (e.g., using LangChain, Lang Graph, Crew AI).</li> <li>Background in edge deployment for computer vision models (TensorRT, ONNX).</li> </ul> <h4>Benefits</h4> <ul> <li>Paid time off</li> <li>Performance bonus</li> <li>Training & development</li> </ul></p><p></p>

<p><h4>Description</h4> <p>BlackStone eIT is actively looking for a dedicated AI team lead to spearhead our artificial intelligence initiatives. This role involves leading a talented team of AI professionals to create innovative AI-driven solutions that align with the company's vision. You will play a crucial part in strategizing, developing, and deploying AI technologies that enhance our products and services while maintaining the highest standards of excellence.</p> <h4>Responsibilities:</h4> <ul> <li>Lead the AI team in designing, developing, and implementing AI models and systems.</li> <li>Collaborate with stakeholders to identify AI opportunities that drive business value.</li> <li>Guide the team to effectively use machine learning frameworks and tools.</li> <li>Oversee project lifecycle from research and prototyping to production deployment.</li> <li>Maintain knowledge of latest trends and advancements in AI and machine learning.</li> <li>Establish best practices and foster a culture of continuous improvement and innovation.</li> </ul> <h4>Requirements</h4> <ul> <li>Experience: 6+ years of hands-on experience in machine learning, deep learning, or AI engineering.</li> <li>3+ years of experience in a technical leadership or mentoring role.</li> <li>Programming & frameworks: Expert-level proficiency in Python and deep learning frameworks (PyTorch is strongly preferred, or TensorFlow).</li> <li>Cloud infrastructure: Extensive, hands-on experience with Microsoft Azure, specifically building training and deployment pipelines using Azure ML workspace, MLflow, and container orchestration (Docker/Kubernetes).</li> <li>NLP expertise: Deep understanding of modern NLP architectures (Transformers, BERT, GPT variants), tokenization, vector databases, and libraries like Hugging Face and LangChain/LangGraph.</li> <li>CV expertise: Strong mathematical foundation in image processing and experience building custom models using OpenCV, YOLO architectures, and PyTorch Vision.</li> <li>MLOps: Proven ability to build CI/CD pipelines for machine learning models, manage model registries, and monitor model drift in production.</li> <li>Experience with building and deploying autonomous AI agents (e.g., using LangChain, LangGraph, Crew AI).</li> <li>Background in edge deployment for computer vision models (TensorRT, ONNX).</li> </ul> <h4>Benefits</h4> <ul> <li>Paid time off</li> <li>Performance bonus</li> <li>Training & development</li> </ul></p><p></p>

<p><h4>Description</h4> <p>BlackStone eIT is actively looking for a dedicated AI team lead to spearhead our artificial intelligence initiatives. This role involves leading a talented team of AI professionals to create innovative AI-driven solutions that align with the company's vision. You will play a crucial part in strategizing, developing, and deploying AI technologies that enhance our products and services while maintaining the highest standards of excellence.</p> <h4>Responsibilities:</h4> <ul> <li>Lead the AI team in designing, developing, and implementing AI models and systems.</li> <li>Collaborate with stakeholders to identify AI opportunities that drive business value.</li> <li>Guide the team to effectively use machine learning frameworks and tools.</li> <li>Oversee project lifecycle from research and prototyping to production deployment.</li> <li>Maintain knowledge of latest trends and advancements in AI and machine learning.</li> <li>Establish best practices and foster a culture of continuous improvement and innovation.</li> </ul> <h4>Requirements</h4> <ul> <li>Experience: 6+ years of hands-on experience in machine learning, deep learning, or AI engineering.</li> <li>3+ years of experience in a technical leadership or mentoring role.</li> <li>Programming & frameworks: Expert-level proficiency in Python and deep learning frameworks (PyTorch is strongly preferred, or TensorFlow).</li> <li>Cloud infrastructure: Extensive, hands-on experience with Microsoft Azure, specifically building training and deployment pipelines using Azure ML workspace, MLflow, and container orchestration (Docker/Kubernetes).</li> <li>NLP expertise: Deep understanding of modern NLP architectures (Transformers, BERT, GPT variants), tokenization, vector databases, and libraries like Hugging Face and LangChain/LangGraph.</li> <li>CV expertise: Strong mathematical foundation in image processing and experience building custom models using OpenCV, YOLO architectures, and PyTorch Vision.</li> <li>MLOps: Proven ability to build CI/CD pipelines for machine learning models, manage model registries, and monitor model drift in production.</li> <li>Experience with building and deploying autonomous AI agents (e.g., using LangChain, LangGraph, Crew AI).</li> <li>Background in edge deployment for computer vision models (TensorRT, ONNX).</li> </ul> <h4>Benefits</h4> <ul> <li>Paid time off</li> <li>Performance bonus</li> <li>Training & development</li> </ul></p><p></p>

<p><h4>BlackStone eIT is actively looking for a dedicated AI team lead to spearhead our artificial intelligence initiatives.</h4> <p>This role involves leading a talented team of AI professionals to create innovative AI-driven solutions that align with the company's vision. You will play a crucial part in strategizing, developing, and deploying AI technologies that enhance our products and services while maintaining the highest standards of excellence.</p> <h4>Responsibilities:</h4> <ul> <li>Lead the AI team in designing, developing, and implementing AI models and systems.</li> <li>Collaborate with stakeholders to identify AI opportunities that drive business value.</li> <li>Guide the team to effectively use machine learning frameworks and tools.</li> <li>Oversee project lifecycle from research and prototyping to production deployment.</li> <li>Maintain knowledge of latest trends and advancements in AI and machine learning.</li> <li>Establish best practices and foster a culture of continuous improvement and innovation.</li> </ul> <h4>Requirements</h4> <ul> <li>Experience: 6+ years of hands-on experience in machine learning, deep learning, or AI engineering.</li> <li>3+ years of experience in a technical leadership or mentoring role.</li> <li>Programming & frameworks: Expert-level proficiency in Python and deep learning frameworks (PyTorch is strongly preferred, or TensorFlow).</li> <li>Cloud infrastructure: Extensive, hands-on experience with Microsoft Azure, specifically building training and deployment pipelines using Azure ML workspace, MLflow, and container orchestration (Docker/Kubernetes).</li> <li>NLP expertise: Deep understanding of modern NLP architectures (Transformers, BERT, GPT variants), tokenization, vector databases, and libraries like Hugging Face and Lang Chain/Lang Graph.</li> <li>CV expertise: Strong mathematical foundation in image processing and experience building custom models using OpenCV, YOLO architectures, and PyTorch Vision.</li> <li>MLOps: Proven ability to build CI/CD pipelines for machine learning models, manage model registries, and monitor model drift in production.</li> <li>Experience with building and deploying autonomous AI agents (e.g., using Langchain, Langgraph, Crew AI).</li> <li>Background in edge deployment for computer vision models (TensorRT, ONNX).</li> </ul> <h4>Benefits</h4> <ul> <li>Paid time off</li> <li>Performance bonus</li> <li>Training & development</li> </ul></p><p></p>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>DevOps Engineer We re a crypto exchange where reliability and security are core to everything we do. We re looking for someone to own our AWS and Cloudflare infrastructure, streamline deployments, and help us maintain the high security standards that come with being ISO 27001 certified.</p><p>What you ll do</p><ul><li>Build and maintain our cloud infrastructure on AWS and Cloudflare networking, compute, storage, security, the works.</li><li>Own our CI/CD pipelines and make shipping code fast and safe.</li><li>Automate everything you can: provisioning, configuration, monitoring, operational tasks.</li><li>Monitor systems, track down issues, and fix them before they become incidents.</li><li>Handle production deployments, rollbacks, and incident response.</li><li>Manage and tune databases backups, replication, performance, and availability.</li><li>Keep our infrastructure secure, backed up, and recoverable.</li><li>Help maintain ISO 27001 compliance and support security audits.</li><li>Write runbooks and document systems so the team isn t guessing at 2am.</li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p>What you need</p><ul><li>3 year Experience as a DevOps Engineer, SRE, Cloud Engineer, or similar you ve done this before.</li><li>Solid hands-on experience with AWS (compute, networking, IAM, storage, monitoring, deployments).</li><li>Comfortable with Linux, shell scripting, and networking fundamentals.</li><li>Experience with Terraform , Terragrunt , Atmos and Atlantis .</li><li>Hands-on with Kubernetes and related technologies such as Istio and Kyverno .</li><li>Experience with a CI/CD tool like GitHub Actions .</li><li>Can debug infrastructure and deployment problems under pressure.</li><li>Experience with Cloudflare (DNS, CDN, WAF, DDoS protection) or similar edge/security platforms.</li><li>Understands cloud security, access management, and disaster recovery.</li><li>Comfortable working within compliance frameworks (ISO 27001 or similar).</li><li>Hands-on database experience performance tuning, backups, replication, failover.</li></ul><p>Nice to have</p><ul><li>Familiarity with monitoring/logging stacks (CloudWatch, Prometheus, Grafana, ELK).</li><li>Experience with caching, load balancing, and high-availability setups.</li><li>Scripting beyond Bash Python or similar.</li><li>Familiarity with AI related tools and technologies AWS or other cloud certifications.</li><li>Experience in fintech, crypto, or other security-sensitive industries.</li><li>Background CS degree or equivalent practical experience in DevOps, cloud infrastructure, or platform engineering.</li></ul><p>We care more about what you can do than where you studied.</p><p></p></section>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>BlackStone eIT is actively looking for a dedicated AI Team Lead to spearhead our Artificial Intelligence initiatives.<br> This role involves leading a talented team of AI professionals to create innovative AI-driven solutions that align with the company's vision.<br> You will play a crucial part in strategizing, developing, and deploying AI technologies that enhance our products and services while maintaining the highest standards of excellence.<br> Responsibilities: Lead the AI team in designing, developing, and implementing AI models and systems.<br> Collaborate with stakeholders to identify AI opportunities that drive business value.<br> Guide the team to effectively use machine learning frameworks and tools.<br> Oversee project lifecycle from research and prototyping to production deployment.<br> Maintain knowledge of latest trends and advancements in AI and machine learning.<br> Establish best practices and foster a culture of continuous improvement and innovation.<br> Paid Time Off Performance Bonus Training &amp; Development Experience: 6+ years of hands-on experience in Machine Learning, Deep Learning, or AI Engineering.<br> 3+ years of experience in a technical leadership or mentoring role.<br> Programming &amp; Frameworks: Expert-level proficiency in Python and deep learning frameworks (PyTorch is strongly preferred, or TensorFlow).<br> Cloud Infrastructure: Extensive, hands-on experience with Microsoft Azure, specifically building training and deployment pipelines using Azure ML workspace, MLflow, and container orchestration (Docker/Kubernetes).<br> NLP Expertise: Deep understanding of modern NLP architectures (Transformers, BERT, GPT variants), tokenization, vector databases, and libraries like Hugging Face and Lang Chain/Lang Graph.<br> CV Expertise: Strong mathematical foundation in image processing and experience building custom models using OpenCV, YOLO architectures, and PyTorch Vision.<br> MLOps: Proven ability to build CI/CD pipelines for machine learning models, manage model registries, and monitor model drift in production.<br> Experience with building and deploying Autonomous AI Agents (e.<br>g., using Langchain,langgraph,Crew ai ).<br> Background in edge deployment for Computer Vision models (TensorRT, ONNX).<br></span> </div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p><span >Key Responsibilities</span></p><ul><li>Lead and mentor a cross-functional data team (engineering, analytics, data science)</li><li>Architect and manage Syarah s data platform on GCP (BigQuery, Cloud Run, Dataform)</li><li>Design scalable ETL pipelines and unified star schema data models</li><li>Integrate ERPNext and other operational systems into centralized data architecture</li><li>Build and deploy containerized services using Docker on Cloud Run</li><li>Develop and maintain Flask REST APIs for secure data sharing</li><li>Own data DevOps , including CI/CD pipelines and infrastructure management</li><li>Orchestrate workflows using Apache Airflow</li><li>Integrate and govern Adjust (mobile attribution) and Mixpanel (product analytics) into a unified data lake</li><li>Ensure reliable event tracking, identity resolution, and funnel analytics across platforms</li><li>Build unified product, payments, and financial data models enabling revenue reconciliation and performance tracking</li><li>Deliver proactive insights: identify trends, anomalies, and risks before they are requested</li><li>Translate data into executive-level business decisions and recommendations</li><li>Define KPI frameworks and build trusted data products for finance, operations, and product teams</li><li>Ensure data accuracy, reliability, and availability through monitoring, alerts, and SLA standards</li><li>Develop internal AI tools using LLMs and prompt engineering to improve productivity and automation</li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>7+ years of experience in data engineering, analytics, or data platform roles</li><li>Proven experience in a data leadership or senior technical role</li><li>Strong expertise in GCP data stack (BigQuery, Cloud Run, Dataform)</li><li>Advanced proficiency in Python and SQL</li><li>Solid experience building and scaling data pipelines and ETL architectures</li><li>Experience with API development (Flask or similar frameworks)</li><li>Hands-on experience with Airflow or other workflow orchestration tools</li><li>Strong knowledge of product analytics and mobile attribution tools (e.g., Mixpanel, Adjust)</li><li>Experience working with ERP systems (ERPNext or similar) is a plus</li><li>Strong understanding of data modeling, KPI frameworks, and business intelligence</li><li>Experience in building or leading data teams</li><li>Strong business acumen with ability to translate data into actionable insights</li><li>Experience with CI/CD, Docker, and cloud infrastructure management</li><li>Exposure to AI/ML tools or LLM-based automation is a strong plus</li><li>Excellent communication skills and ability to work closely with executive leadership</li></ul><p></p></section>

<p><h4>Job purpose</h4> <p>As a senior DevOps engineer, you will own the design, reliability, and scalability of our cloud-based production systems. You will lead the architecture, automation, and operation of our Azure/AWS infrastructure, drive security, performance, and cost efficiency across our platforms, and set DevOps standards and best practices for the team. You will act as a technical authority on cloud operations, mentor junior engineers, and partner with engineering leadership to shape the platform roadmap.</p> <h4>Duties & responsibilities</h4> <h4>Cloud system operations</h4> <ul> <li>Lead the design, deployment, and operation of Azure/AWS cloud-based production systems.</li> <li>Own system performance, incident response, and root-cause analysis across production applications.</li> <li>Define release engineering and pre-production validation standards to ensure system quality and functionality.</li> <li>Architect and enforce backup, disaster recovery, and cost optimization (FinOps) strategies across cloud environments.</li> <li>Lead container orchestration and workload management on AKS/Kubernetes clusters, including upgrades, scaling, and hardening.</li> </ul> <h4>Automation and scripting</h4> <ul> <li>Design and maintain enterprise-grade automation frameworks for operational and platform processes.</li> <li>Build reusable tooling and scripts (e.g., Python, Bash, PowerShell) for automation, observability, and incident response.</li> <li>Lead GitOps adoption and continuous-delivery practices using ArgoCD or Flux.</li> </ul> <h4>Security and compliance</h4> <ul> <li>Define and enforce cloud security best practices, IAM policies, and secrets management across environments.</li> <li>Establish and maintain security protocols and compliance posture (e.g., ISO 27001, SOC 2 controls relevant to infrastructure).</li> </ul> <h4>Monitoring and metrics</h4> <ul> <li>Architect and operate observability platforms (metrics, logging, tracing) across Azure/AWS, defining SLOs, SLIs, and alerting strategy.</li> <li>Drive operational excellence by analyzing reliability metrics and leading post-incident reviews and improvement initiatives.</li> </ul> <h4>Research and evaluation</h4> <ul> <li>Evaluate and recommend emerging technologies, tools, and architectural patterns for adoption.</li> <li>Lead vendor and product evaluations, including proofs-of-concept and total-cost-of-ownership analysis.</li> </ul> <h4>Communication and collaboration</h4> <ul> <li>Mentor junior and mid-level DevOps engineers through code reviews, pairing, and technical guidance.</li> <li>Partner with engineering, security, and product stakeholders to define technical requirements and influence platform direction.</li> <li>Communicate effectively with executive and technical audiences on cloud strategy, risk, and roadmap.</li> </ul> <h4>Education, experience & qualifications</h4> <ul> <li>Bachelor’s degree in computer science, information systems, or a related field.</li> <li>6+ years of hands-on experience in DevOps, cloud engineering, or SRE roles, including 3+ years with primary focus on Microsoft Azure (required).</li> <li>Expert-level Kubernetes administration, including cluster lifecycle management, upgrades, networking, and security hardening.</li> <li>Production experience operating Azure Kubernetes Service (AKS) at scale.</li> <li>Strong experience designing and maintaining infrastructure as code with Terraform, including module design and state management.</li> <li>Deep experience designing and operating CI/CD pipelines (e.g., GitHub Actions, Azure DevOps, GitLab CI).</li> <li>Hands-on experience with observability stacks (Prometheus, Grafana, Azure Monitor, ELK, or similar), including dashboard and alert design.</li> <li>Strong Linux system administration knowledge.</li> <li>Experience working with GitOps tools such as ArgoCD or Flux.</li> <li>Working knowledge of database administration in production (backups, performance tuning, HA/DR, and troubleshooting).</li> <li>Strong scripting and automation skills in Python, Bash, and/or PowerShell.</li> <li>Strong analytical and problem-solving abilities.</li> <li>Ability to collaborate effectively within cross-functional teams.</li> <li>Clear and precise documentation and communication skills.</li> <li>Fluency in both English and Arabic (spoken and written).</li> </ul> <h4>Behavioral competencies</h4> <ul> <li>Initiative</li> <li>Problem solving</li> <li>Team oriented</li> <li>Adaptability</li> <li>Ability to work under pressure</li> </ul> <h4>Technical competencies</h4> <ul> <li>Cloud computing fundamentals</li> <li>Linux operating systems</li> <li>Networking protocols and topologies</li> <li>Scripting and automation</li> <li>Monitoring and logging tools</li> <li>Security best practices</li> <li>System troubleshooting</li> <li>Backup and disaster recovery concepts</li> <li>Container orchestration (AKS / Kubernetes)</li> <li>GitOps (ArgoCD, Flux)</li> <li>Database administration</li> </ul></p><p></p>

<p><h4>Job purpose</h4> <p>As a senior DevOps engineer, you will own the design, reliability, and scalability of our cloud-based production systems. You will lead the architecture, automation, and operation of our Azure/AWS infrastructure, drive security, performance, and cost efficiency across our platforms, and set DevOps standards and best practices for the team. You will act as a technical authority on cloud operations, mentor junior engineers, and partner with engineering leadership to shape the platform roadmap.</p> <h4>Duties & responsibilities</h4> <h4>Cloud system operations</h4> <ul> <li>Lead the design, deployment, and operation of Azure/AWS cloud-based production systems.</li> <li>Own system performance, incident response, and root-cause analysis across production applications.</li> <li>Define release engineering and pre-production validation standards to ensure system quality and functionality.</li> <li>Architect and enforce backup, disaster recovery, and cost optimization (FinOps) strategies across cloud environments.</li> <li>Lead container orchestration and workload management on AKS/Kubernetes clusters, including upgrades, scaling, and hardening.</li> </ul> <h4>Automation and scripting</h4> <ul> <li>Design and maintain enterprise-grade automation frameworks for operational and platform processes.</li> <li>Build reusable tooling and scripts (e.g., Python, Bash, PowerShell) for automation, observability, and incident response.</li> <li>Lead GitOps adoption and continuous-delivery practices using ArgoCD or Flux.</li> </ul> <h4>Security and compliance</h4> <ul> <li>Define and enforce cloud security best practices, IAM policies, and secrets management across environments.</li> <li>Establish and maintain security protocols and compliance posture (e.g., ISO 27001, SOC 2 controls relevant to infrastructure).</li> </ul> <h4>Monitoring and metrics</h4> <ul> <li>Architect and operate observability platforms (metrics, logging, tracing) across Azure/AWS, defining SLOs, SLIs, and alerting strategy.</li> <li>Drive operational excellence by analyzing reliability metrics and leading post-incident reviews and improvement initiatives.</li> </ul> <h4>Research and evaluation</h4> <ul> <li>Evaluate and recommend emerging technologies, tools, and architectural patterns for adoption.</li> <li>Lead vendor and product evaluations, including proofs-of-concept and total-cost-of-ownership analysis.</li> </ul> <h4>Communication and collaboration</h4> <ul> <li>Mentor junior and mid-level DevOps engineers through code reviews, pairing, and technical guidance.</li> <li>Partner with engineering, security, and product stakeholders to define technical requirements and influence platform direction.</li> <li>Communicate effectively with executive and technical audiences on cloud strategy, risk, and roadmap.</li> </ul> <h4>Education, experience & qualifications</h4> <ul> <li>Bachelor’s degree in computer science, information systems, or a related field.</li> <li>6+ years of hands-on experience in DevOps, cloud engineering, or SRE roles, including 3+ years with primary focus on Microsoft Azure (required).</li> <li>Expert-level Kubernetes administration, including cluster lifecycle management, upgrades, networking, and security hardening.</li> <li>Production experience operating Azure Kubernetes Service (AKS) at scale.</li> <li>Strong experience designing and maintaining infrastructure as code with Terraform, including module design and state management.</li> <li>Deep experience designing and operating CI/CD pipelines (e.g., GitHub Actions, Azure DevOps, GitLab CI).</li> <li>Hands-on experience with observability stacks (Prometheus, Grafana, Azure Monitor, ELK, or similar), including dashboard and alert design.</li> <li>Strong Linux system administration knowledge.</li> <li>Experience working with GitOps tools such as ArgoCD or Flux.</li> <li>Working knowledge of database administration in production (backups, performance tuning, HA/DR, and troubleshooting).</li> <li>Strong scripting and automation skills in Python, Bash, and/or PowerShell.</li> <li>Strong analytical and problem-solving abilities.</li> <li>Ability to collaborate effectively within cross-functional teams.</li> <li>Clear and precise documentation and communication skills.</li> <li>Fluency in both English and Arabic (spoken and written).</li> </ul> <h4>Behavioral competencies</h4> <ul> <li>Initiative</li> <li>Problem solving</li> <li>Team oriented</li> <li>Adaptability</li> <li>Ability to work under pressure</li> </ul> <h4>Technical competencies</h4> <ul> <li>Cloud computing fundamentals</li> <li>Linux operating systems</li> <li>Networking protocols and topologies</li> <li>Scripting and automation</li> <li>Monitoring and logging tools</li> <li>Security best practices</li> <li>System troubleshooting</li> <li>Backup and disaster recovery concepts</li> <li>Container orchestration (AKS / Kubernetes)</li> <li>GitOps (ArgoCD, Flux)</li> <li>Database administration</li> </ul></p><p></p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Description</span><br><span></span><p><span><span>MedNet Jordan is one of the leading managed care service organizations that caters to healthcare needs. We are currently seeking to hire a </span></span><span><span><strong>Senior Quality Engineer</strong></span></span><span><span> (on <strong>Hybrid working modules</strong> basis) with the following tasks and responsibilities:</span></span></p><br><p><span><span><strong>Your Job:</strong></span></span></p><br><p><span><span><strong>Key Responsibilities</strong></span></span></p><br><ul><li><span><span>Analyze business and system requirements and develop comprehensive test plans, test cases, and test scenarios.</span></span></li><li><span><span>Execute manual testing activities and ensure full validation of application functionality and performance.</span></span></li><li><span><span>Identify, log, track, and manage defects through their lifecycle until resolution.</span></span></li><li><span><span>Perform backend validation including database checks and data integrity verification using SQL queries.</span></span></li><li><span><span>Ensure full coverage of requirements and mitigate risks throughout the SDLC.</span></span></li><li><span><span>Maintain proper documentation for test artifacts, execution reports, and defect logs.</span></span></li><li><span><span>Participate in Agile ceremonies (stand-ups, sprint planning, retrospectives).</span></span></li><li><span><span>Collaborate closely with developers, architects, business analysts, and stakeholders.</span></span></li><li><span><span><strong>Leverage automation where applicable to improve test efficiency and coverage.</strong></span></span></li><li><span><span>Continuously enhance QA processes, standards, and methodologies.</span></span></li></ul><p><span><span><strong>Communication &amp; Working Relationships</strong></span></span></p><br><ul><li><span>Work closely with development teams to validate features and ensure defect resolution.</span></li><li><span>Collaborate with business teams and analysts to clarify requirements.</span></li><li><span>Coordinate with QA team members and architects to align testing strategies.</span></li><li><span>Communicate testing progress, risks, and results effectively</span></li></ul><br> <br> <span>Qualifications</span><br><span></span><p><strong>Your Profile:</strong></p><br><ul><li><span><span>Bachelor’s degree in Computer Science, Software Engineering, or a related discipline.</span></span></li><li><span><span>4–7 years of experience in software testing and quality assurance.</span></span></li><li><span><span>Experience working in Agile/Scrum and SDLC environments.</span></span></li><li><span><span>Experience in test automation and quality validation processes.</span></span></li><li><span><span>Test planning, test case design, and defect management</span></span></li><li><span><span>Strong understanding of SDLC and QA best practices</span></span></li><li><span><span>Manual testing and validation techniques</span></span></li><li><span><span>Database validation and SQL querying</span></span></li><li><span><span>Jira and defect tracking workflows</span></span></li><li><span><span>Strong analytical and communication skills</span></span></li><li><span><span>Experience with automation frameworks such as Selenium, Playwright, or Pytest</span></span></li><li><span><span>Programming/scripting knowledge (Java, Python, JavaScript/TypeScript)</span></span></li><li><span><span>API testing tools (Postman)</span></span></li><li><span><span>Familiarity with test management tools (X-Ray, Zephyr)</span></span></li><li><span><span>Knowledge of CI/CD pipelines and integration testing</span></span></li></ul><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span><u><b><span><span>About the Job&nbsp; <br></span></span></b></u><br><span><span>As a&nbsp;</span></span><b><span><span>Full Stack Engineer&nbsp;</span></span></b><span><span>at Aspire,&nbsp;you will&nbsp;play a pivotal role in shaping digital solutions that drive performance and provide an unparalleled user experience.</span></span><br><u><b><span><span>What you’ll do</span></span></b></u><br></span><ul><li><span><span><span>Participate actively in designing and implementing full-stack applications, handling both frontend and backend components.</span></span></span></li><li><span><span><span>Produce clean, efficient code and engage in code reviews to maintain quality and consistency across the team.</span></span></span></li><li><span><span><span>Address and resolve intricate software issues to ensure smooth and consistent performance.</span></span></span></li></ul><b><u><span><span>What you’ll need<br></span></span></u></b><br><ul><li><span><span><span>Bachelor's degree in Computer Science, Engineering, or a related field.</span></span></span></li><li><span><span><span>Minimum 3 years of experience in Full-Stack Development.&nbsp;</span></span></span></li><li><span><span><span>Experience in designing, developing, and maintaining web applications from start to finish.</span></span></span></li><li><span><span><span>Experience in back-end technologies and frameworks, such as Java, Python, Kotlin.</span></span></span></li><li><span><span><span>Experience in front-end technologies and frameworks, such as React, Angular.</span></span></span></li><li><span><span><span>Experience working with RESTful APIs and integrating third-party services.</span></span></span></li><li><span><span><span>Strong problem-solving skills and the ability to think critically.</span></span></span></li><li><span><span><span>Excellent communication and teamwork skills to collaborate effectively with cross-functional teams.</span></span></span></li><li><span><span>Awareness or knowledge of IT security best practices as defined by ISO/SOC or similar.</span></span></li></ul><b><u><span><span>Why Aspire</span></span></u></b><br><span><span>In addition to a competitive long-term total compensation with salary and performance-based&nbsp;bonus, we have a reward philosophy that expands beyond this.&nbsp;</span></span><br><ul><li><span><span><span>Be part of a (Remote is here-to stay) organization.</span></span></span></li><li><span><span><span>Work and learn from great minds.</span></span></span></li><li><span><span><span>Explore new opportunities to learn and grow everyday by attending technical and nontechnical training.</span></span></span></li><li><span><span><span>Get market exposure by working with international tech leaders.&nbsp;</span></span></span></li><li><span><span><span>Nursery reimbursement benefit.&nbsp;</span></span></span><br></li><li><span><span><span>Attend virtual and onsite international tech conference.</span></span></span></li><li><span><span>Exposure to work in an IT environment that adheres to rigorous security and compliance standards defined by ISO/SOC</span></span></li></ul><br> </div>

<p><h4>Role overview</h4> <p>We are seeking a highly skilled senior AI infrastructure and platform engineer to join our client’s team in Riyadh. In this role, you’ll be responsible for building, managing, and optimizing scalable AI infrastructure and compute environments that support high-performance workloads, including GPU-accelerated AI/ML pipelines, cluster scheduling, and orchestration.</p> <h4>Key responsibilities</h4> <ul> <li>Deploy, maintain, and optimize GPU-based compute clusters and infrastructure.</li> <li>Manage and operate GPU orchestration tools and platforms such as: <ul> <li>Nvidia Base Command Manager (critical)</li> <li>Nvidia AI Enterprise Suite</li> <li>Nvidia GPU and Network Operators</li> <li>Nvidia NIMs and Blueprints</li> </ul> </li> <li>Configure, deploy, and maintain compute workloads using scheduling and orchestration tools including: <ul> <li>Slurm (critical)</li> <li>Vanilla Kubernetes</li> </ul> </li> <li>Install, configure, and maintain the underlying OS (e.g. Canonical Ubuntu) and supporting system software.</li> <li>Monitor and troubleshoot infrastructure performance, availability, and reliability; ensure high uptime for AI/ML workloads.</li> <li>Work with data scientists, ML engineers, and development teams to define infrastructure requirements, resource allocation, and deployment workflows.</li> <li>Develop automation scripts, CI/CD pipelines, and best practices for infrastructure provisioning and management.</li> <li>Document architecture, configurations, and operational procedures; enforce security, compliance, and backup policies.</li> </ul> <h4>Requirements</h4> <h5>Required skills & experience</h5> <ul> <li>Proven experience managing GPU-based AI/ML infrastructure and compute clusters.</li> <li>Hands-on experience with: <ul> <li>Nvidia Base Command Manager</li> <li>Nvidia AI Enterprise Suite</li> <li>Nvidia GPU/Network Operators, NIMs, Blueprints</li> </ul> </li> <li>Strong experience with Slurm and/or Kubernetes orchestration.</li> <li>Solid Linux system administration skills — preferably on Ubuntu or similar distributions.</li> <li>Strong scripting/automation ability (e.g. Bash, Python, or relevant tooling) for provisioning, deployment, and maintenance.</li> <li>Excellent troubleshooting and performance-tuning skills.</li> <li>Experience collaborating with ML/data science teams and integrating infrastructure with their workflows.</li> <li>Strong understanding of networking, security, resource allocation, and cluster management best practices.</li> </ul> <h5>Preferred qualifications</h5> <ul> <li>Previous experience working in a high-performance computing (HPC) or AI-focused infrastructure team.</li> <li>Knowledge of containerization, container orchestration, and GPUs in cloud or on-prem environments.</li> <li>Experience with CI/CD, infrastructure-as-code (e.g. Terraform, Ansible), monitoring tools, and logging setups.</li> <li>Familiarity with workload scheduling, job queuing, resource quotas, and GPU-shared environments.</li> </ul></p><p></p>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>We are looking for a talented Sr. Specialist. Data Scientist to join us. At Hikma you ll be supported by a culture of progress and belonging where people are encouraged to develop, wellbeing is prioritised and our inclusive approach values contributions from all. We re seeking candidates who embody our values: Innovative, driven to keep learning; Caring, genuinely compassionate in their work; and Collaborative, eager to solve problems together.</p><p>If you want to be part of a team that cares about impact, this is the place for you.</p><h3>Key Responsibilities:</h3><ul><li>Develop and deploy machine learning models to enhance financial forecasting, anomaly detection, and predictive analytics.</li><li>Work with large datasets from SAP ECC, ERP systems, and external sources, integrating them into Azure Databricks for analytics.</li><li>Collaborate with finance, accounting, and business teams to understand challenges and develop data-driven solutions.</li><li>Design and optimize data pipelines to enable ML model training, validation, and deployment.</li><li>Utilize LLM, NLP, time-series analysis, and deep learning where applicable to extract insights from structured and unstructured data.</li><li>Develop interactive dashboards and visualizations to communicate insights to finance and business stakeholders.</li><li>Ensure data quality, governance, and compliance while handling sensitive financial data.</li><li>Utilize automation tools such as Selenium to streamline data collection and processing workflows</li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p>We are looking for candidates whose experience and skills align closely with the qualifications outlined below:</p><p>Minimum: Bachelor s in Data Science, Computer Science, Statistics, Mathematics, or a related field.</p><p>Preferred: Master s degree in Data Science or a related field.</p><p>At least 4-7 years experience in data science and machine learning.</p><p>Experience in a Finance department is plus.</p><h3>Skills:</h3><p>Strong proficiency in Python (including Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).</p><p>Experience with Databricks and Azure Databricks for large scale data processing and ML model deployment.</p><p>Hands-on experience with SQL and working with relational databases.</p><p>Knowledge of big data processing frameworks such as PySpark.</p><p>Expertise in ETL/ELT processes and working with structured and unstructured datasets.</p><p>Experience with data visualization tools such as Power BI, Tableau.</p><p>Strong problem-solving, analytical, and critical-thinking skills.</p><p>Experience with LLMs and NLP-based solutions for data enrichment and smart automation.</p><p>Proficiency in English, both written and verbal, for effective communication with finance and business stakeholders.</p><p></p></section>

<p>The Senior DevOps Engineer executes and refines the DevOps strategy and is instrumental in implementing automation and integration across IT Operations, Application Delivery, Development, and Data Warehousing, ensuring alignment with the organization's DevOps methodology. As a senior member of the team, the role also sets technical standards and mentors junior engineers.</p><p><strong>Main Activities and Responsibilities:</strong></p><ul><li>Design, implement, and maintain scalable CI/CD pipelines using GitHub Actions, following GitOps methodology with ArgoCD to enable reliable and automated Kubernetes deployments.</li><li>Automate infrastructure provisioning and configuration using Terraform, CloudFormation, and Ansible.</li><li>Manage and optimize AWS infrastructure including networking, IAM, EC2, EKS, RDS, MSK, ElastiCache, and Route53, with a strong focus on automation, security, and cost optimization.</li><li>Deploy and operate Kubernetes (Amazon EKS) workloads using Helm, Kustomize, and Karpenter, ensuring consistent configuration and efficient cluster autoscaling across environments.</li><li>Implement and maintain monitoring, logging, and alerting solutions using Prometheus, Grafana, Zabbix, Graylog, and JSM/OpsGenie.</li><li>Support and maintain database and data platform infrastructure (MySQL, PostgreSQL, MongoDB, Redshift), ensuring high availability, performance, monitoring, backup, and disaster recovery.</li><li>Manage edge and application security using Cloudflare and enforce secrets management and IAM governance across environments.</li><li>Investigate production incidents, perform root cause analysis, implement preventive actions, and participate in the on-call escalation rotation to drive continuous service reliability improvements.</li><li>Collaborate with other departments and engineering teams to improve processes, automation, and operational excellence.</li><li>Maintain technical documentation and define and review technical standards for infrastructure and automation.</li><li>Maintain technical documentation and automate operational processes such as backup and disaster recovery.</li></ul><p><strong>Required Skills &amp; Experience:</strong></p><ul><li>5+ years of experience in DevOps, AWS Cloud Engineering, or similar roles.</li><li>Strong experience with CI/CD pipeline design and automation using GitHub Actions, ArgoCD, and GitOps workflows.</li><li>Hands-on experience with AWS services including VPC, IAM, EC2, EKS, RDS, MSK, ElastiCache, and Route53.</li><li>Proficiency with Infrastructure as Code tools such as Terraform, CloudFormation, or Ansible.</li><li>Experience managing and operating Kubernetes clusters (preferably EKS), deploying applications with Helm or Kustomize, and configuring cluster autoscaling with Karpenter.</li><li>Strong understanding of containerization with Docker.</li><li>Proficiency scripting in Bash and/or Python for automation.</li><li>Experience implementing monitoring, logging, and alerting solutions using Prometheus, Grafana, Zabbix, Graylog, or similar platforms.</li><li>Solid understanding of Linux and networking concepts.</li><li>Familiarity with Windows Server a plus.</li><li>Experience with incident management, troubleshooting production systems, and root cause analysis.</li><li>Experience with databases and data platforms such as PostgreSQL, MySQL, MongoDB, and Redshift.</li><li>Clear written communication and experience working in distributed teams</li></ul><p><strong>Further Info:</strong></p><ul><li>Working hours are 08:30 17.00 Sunday to Thursday</li><li>The role is in Jordan</li><li>Friendly and fun working environment</li><li>Hybrid working</li><li>Flexitime</li><li>A competitive compensation package which includes great benefits</li></ul><p><strong>Desired Candidate Profile</strong></p><p>The Senior DevOps Engineer executes and refines the DevOps strategy and is instrumental in implementing automation and integration across IT Operations, Application Delivery, Development, and Data Warehousing, ensuring alignment with the organization's DevOps methodology. As a senior member of the team, the role also sets technical standards and mentors junior engineers.</p><p><strong>Main Activities and Responsibilities:</strong></p><ul><li>Design, implement, and maintain scalable CI/CD pipelines using GitHub Actions, following GitOps methodology with ArgoCD to enable reliable and automated Kubernetes deployments.</li><li>Automate infrastructure provisioning and configuration using Terraform, CloudFormation, and Ansible.</li><li>Manage and optimize AWS infrastructure including networking, IAM, EC2, EKS, RDS, MSK, ElastiCache, and Route53, with a strong focus on automation, security, and cost optimization.</li><li>Deploy and operate Kubernetes (Amazon EKS) workloads using Helm, Kustomize, and Karpenter, ensuring consistent configuration and efficient cluster autoscaling across environments.</li><li>Implement and maintain monitoring, logging, and alerting solutions using Prometheus, Grafana, Zabbix, Graylog, and JSM/OpsGenie.</li><li>Support and maintain database and data platform infrastructure (MySQL, PostgreSQL, MongoDB, Redshift), ensuring high availability, performance, monitoring, backup, and disaster recovery.</li><li>Manage edge and application security using Cloudflare and enforce secrets management and IAM governance across environments.</li><li>Investigate production incidents, perform root cause analysis, implement preventive actions, and participate in the on-call escalation rotation to drive continuous service reliability improvements.</li><li>Collaborate with other departments and engineering teams to improve processes, automation, and operational excellence.</li><li>Maintain technical documentation and define and review technical standards for infrastructure and automation.</li><li>Maintain technical documentation and automate operational processes such as backup and disaster recovery.</li></ul><p><strong>Required Skills &amp; Experience:</strong></p><ul><li>5+ years of experience in DevOps, AWS Cloud Engineering, or similar roles.</li><li>Strong experience with CI/CD pipeline design and automation using GitHub Actions, ArgoCD, and GitOps workflows.</li><li>Hands-on experience with AWS services including VPC, IAM, EC2, EKS, RDS, MSK, ElastiCache, and Route53.</li><li>Proficiency with Infrastructure as Code tools such as Terraform, CloudFormation, or Ansible.</li><li>Experience managing and operating Kubernetes clusters (preferably EKS), deploying applications with Helm or Kustomize, and configuring cluster autoscaling with Karpenter.</li><li>Strong understanding of containerization with Docker.</li><li>Proficiency scripting in Bash and/or Python for automation.</li><li>Experience implementing monitoring, logging, and alerting solutions using Prometheus, Grafana, Zabbix, Graylog, or similar platforms.</li><li>Solid understanding of Linux and networking concepts.</li><li>Familiarity with Windows Server a plus.</li><li>Experience with incident management, troubleshooting production systems, and root cause analysis.</li><li>Experience with databases and data platforms such as PostgreSQL, MySQL, MongoDB, and Redshift.</li><li>Clear written communication and experience working in distributed teams</li></ul>

<p>1. JOB DETAILS:</p><p>Job Title: Analyst, ML Engineer</p><p>Reports to: Sr. Manager, IT Digital Platforms &amp; Digital Transformation</p><p>Department: IT Applications</p><p>Function: IT Applications</p><p>Company: Hikma Holding</p><p>2. JOB PURPOSE:</p><p>The ML Engineer is responsible for supporting the development, testing, and deployment of machine learning models and AI-powered pipelines across Hikma Pharmaceuticals. Working as part of the AI team under the Sr. Manager, IT Digital Platforms &amp; Digital Transformation, and under the close guidance of the AI Architect and AI developers team, this role provides hands-on ML engineering support across the solution lifecycle from data preparation and model experimentation through to deployment and monitoring. The ML Engineer is expected to develop their machine learning and data engineering skills rapidly within a structured team environment, contributing to Hikma's enterprise AI transformation while building foundational expertise in regulated pharmaceutical AI delivery.</p><p>3. JOB DIMENSIONS:</p><p>Number of Staff Supervised: Direct Reports Count: 0 (0 vacant)</p><p>Indirect Reports Count: N/A</p><p>Financial Budget (USD): Supports AI initiative delivery under team supervision</p><p>4. KEY ACCOUNTABILITIES:</p><p>ML Model Development &amp; Experimentation</p><ul><li>Support the development, training, and evaluation of machine learning models under the guidance of the AI Architect and senior team members, following approved architecture standards and initiative briefs</li><li>Assist in ML experimentation activities including data exploration, feature engineering, model selection, and performance evaluation using standard frameworks and cloud AI services</li><li>Apply foundational ML techniques across classical machine learning, NLP, and generative AI domains relevant to Hikma's business areas including Supply Chain, Quality, HR, and Commercial</li><li>Support the implementation of LLM-based solutions including RAG pipelines, prompt engineering, and embedding-based retrieval under senior technical guidance</li><li>Maintain experiment tracking logs, model versioning records, and reproducibility documentation using tools such as ML flow or Azure Machine Learning</li><li>Produce clear and accurate model development artefacts including experiment summaries, performance reports, and model documentation</li></ul><p>Data Engineering &amp; Feature Development</p><ul><li>Assist in building and maintaining ML data pipelines covering data ingestion, transformation, validation, and basic feature engineering for model training and inference workflows</li><li>Support data quality checks, anomaly detection, and dataset preparation activities to ensure ML model inputs meet required standards</li><li>Collaborate with the Data &amp; Analytics team to access and understand available data assets, following data governance and privacy guidelines</li><li>Work with structured data sources including relational databases and enterprise system extracts, developing proficiency in handling diverse data types over time</li></ul><p>ML-Ops &amp; Production Support</p><ul><li>Support the implementation and maintenance of ML-Ops pipeline components including model packaging, deployment, and basic performance monitoring under senior team guidance</li><li>Assist in deploying ML models to cloud environments using approved tooling (Azure Machine Learning, ML-flow, Docker, or equivalent)</li><li>Monitor deployed models for observable performance issues and flag anomalies to the AI Architect or senior team members for investigation</li><li>Maintain accurate records in model registries including versioning and change logs across AI initiatives</li><li>Contribute to the documentation and validation support activities for ML models deployed in GxP-regulated contexts, following defined compliance processes</li></ul><p>Quality Assurance &amp; Testing</p><ul><li>Support the development and execution of testing activities for ML solutions, including data, pipeline tests, model performance checks, and basic integration testing</li><li>Actively participate in code reviews and technical walkthroughs, applying feedback to improve code quality and engineering practices</li><li>Document assigned ML components clearly including data preparation steps, model configurations, test results, and known issues</li><li>Identify and escalate technical issues encountered across the ML stack in a timely and structured manner</li></ul><p>5. Behavioural Competencies:</p><p>Initiative &amp; Drive for Results - Very Good</p><p>Change &amp; Innovation - Very Good</p><p>Communication &amp; Influence - Good</p><p>Developing &amp; Empowering others - Good</p><p>Problem Solving &amp; decision Making - Excellent</p><p>Strategic Thinking - Good</p><p>6. Technical Competencies:</p><p>ML Model Development &amp; Experimentation - Good</p><p>Python &amp; ML Frameworks (PyTorch, TensorFlow, scikit-learn, HuggingFace) - Good</p><p>MLOps &amp; Model Lifecycle Tooling - Good</p><p>Data Engineering &amp; Pipeline Support - Good</p><p>Cloud AI/ML Services (Azure ML) - Good</p><p>Generative AI &amp; LLM Development (RAG, LangChain, Semantic Kernel) - Very Good</p><p>Model Explainability &amp; Responsible AI Awareness - Very Good</p><p>Containerization &amp; CI/CD Basics (Docker, Git, Azure DevOps) - Good</p><p>7. COMMUNICATIONS &amp; WORKING RELATIONSHIPS:</p><p>Internal: AI Champions Network, AI Architect, AI Developer, Data &amp; Analytics Team</p><p>External: AI/ML Vendors &amp; Solution Providers, Implementation Partners, Open Source &amp; Developer Communities</p><p><strong>Desired Candidate Profile</strong></p><ul><li>Bachelor's degree in computer science, Software Engineering, Data Science, Mathematics, Statistics, or related technical field *(Required)*</li><li>Master's degree in Artificial Intelligence, Machine Learning, Data Science, or Computer Science *(Preferred)*</li><li>Microsoft Azure AI Engineer Associate, AWS Machine Learning Specialty, or Google Professional ML Engineer certification *(Preferred)*</li><li>Relevant ML/AI certifications (e.g., DeepLearning.AI ML Specialization, Databricks ML Associate, fast.ai) *(Preferred)*</li><li>0-1 year of professional experience in software development, data science, machine learning, or a related technical field (fresh graduates are welcome to apply)</li><li>Demonstrated hands-on experience with ML model development through academic projects, internships, capstone projects, hackathons, or personal projects</li><li>Familiarity with cloud AI/ML platforms (Azure, AWS, or GCP) gained through coursework, self-study, or practical experimentation *(Preferred)*</li><li>Any exposure to generative AI, LLM tools, or RAG concepts through academic or personal projects *(Preferred)*</li><li>Pharmaceutical, healthcare, life sciences, or other regulated industry exposure *(Preferred but not expected)*</li><li>Working knowledge of Python and foundational ML/DL libraries including scikit-learn, pandas, NumPy, and at least one deep learning framework</li><li>Practical exposure to training and evaluating ML models including classical machine learning and at least one of: NLP, computer vision, or time-series analysis through academic, personal, or internship projects</li><li>Basic familiarity with generative AI concepts including Large Language Models, prompt engineering, and RAG principles *(Preferred)*</li><li>Awareness of ML-Ops concepts and tools such as ML-flow or Azure Machine Learning for experiment tracking and model management *(Preferred)*</li><li>Basic experience with data preparation, cleaning, transformation, and exploratory data analysis using Python</li><li>Familiarity with version control using Git and basic software development practices including code reviews and testing</li><li>Basic understanding of cloud platforms (Azure, AWS, or GCP) and awareness of cloud-based AI/ML services *(Preferred)*</li><li>Familiarity with containerization concepts (Docker) and CI/CD basics *(Preferred)*</li><li>Awareness of responsible AI principles, data privacy regulations (GDPR, HIPAA), and IT security practices relevant to ML development</li><li>Any familiarity with pharmaceutical business processes or GxP compliance in a technology context is a plus *(Preferred)*</li></ul>