Mining engineer Jobs
672 Jobs Found
<h2 class="h5">Job description</h2>
<div class="t-break" data-jb-field="description">
<p>Our Mission is to Simplify Life. We are looking to Simplify and automate complex decision-making for customer centric industries, like Utilities, Financial Services, Logistics, and commerce, that drive the world's economies and you have the chance to join the revolution. We are trying to solve huge challenges in today's enterprise that are directly impacting the employee and customer experience.</p><p><br></p><p>Avertra’s DevOps team is responsible for building and maintaining a modern, scalable, highly available infrastructure to power up our products and service for our clients all over the world. We are looking for a skilled DevOps Engineer who has strong practical troubleshooting skills, advanced overall systems knowledge, public clouds, and provisioning tools. The successful candidate will be responsible for:</p><p>● Designing, building, shipping, and maintaining distributed systems.</p><p>● Building Monitoring, logging, alerting around our infrastructure and applications.</p><p>● Improving the reliability of our systems and CI/CD pipelines both internally and for our customers.</p><p>● Putting everything into code.</p><p>● Plan for reliability by designing systems to work across our multi-region and multi-cloud environments.</p><p>● Working in close collaboration with multi-functional teams.</p><p>● Technical writing / Documentation.</p><p>● Vendor Management.</p><p><br></p><p><b>Main Job Responsibilities:</b></p><p><b></b></p><p><b>Continuous Integration and Deployment:</b></p><p>• Implement and maintain automated build, test, and deployment pipelines using industry-standard tools such as Jenkins, Travis CI, or GitLab CI/CD, Azure DevOps…etc.</p><p>• Design and configure continuous integration and delivery workflows to enable frequent and reliable releases of software applications.</p><p><br></p><p><b>Infrastructure Automation:</b></p><p>• Develop and maintain infrastructure-as-code using tools like Terraform, Ansible, or CloudFormation to automate the provisioning and configuration of cloud-based environments.</p><p>• Implement and manage containerization technologies like Docker and orchestration platforms like Kubernetes for scalable and resilient application deployments.</p><p><br></p><p><b>Monitoring and Performance Optimization:</b></p><p>• Monitor system performance and troubleshoot issues related to scalability, reliability, and availability.</p><p>• Implement and configure monitoring tools such as Prometheus, Grafana, New Relic, or ELK Stack to proactively identify bottlenecks and optimize system performance.</p><p><br></p><p><b>Collaboration and Communication:</b></p><p>• Collaborate with cross-functional teams, including developers, system administrators, and quality assurance, to improve the development and deployment processes.</p><p>• Act as a bridge between development and operations teams, facilitating effective communication and knowledge sharing.</p><p><br></p><p><b>Security and Compliance:</b></p><p>• Implement and enforce security best practices throughout the software development lifecycle.</p><p>• Ensure compliance with relevant regulations, industry standards, and internal policies.</p><p><br></p><p><b>Documentation and Knowledge Sharing:</b></p><p>• Document infrastructure configurations, deployment processes, and troubleshooting guidelines.</p><p>• Contribute to internal knowledge sharing initiatives and help in developing best practices within the organization.</p> </div><h2 class="h5">Skills</h2>
<div data-jb-field="skills"><p><b>Experience: </b></p><p><br></p><p>● 5+ years of relevant of hands-on experience in the DevOps industry</p><p>● Containerization (Kubernetes and OpenShift)</p><p>● Configuration tools and frameworks (Terraform, Istio, Helm)</p><p>● Knowledge of systems (Linux, GNU tooling), networking (OSI model, DNS, routing, SSL Certificates) and virtualization vs containerization</p><p>● Public clouds: AWS/Azure/GCP/Mendix</p><p>● Security Awareness</p><p>● Experience with CI/CD concepts</p><p>● Experience in conducting IT audits, both internal and external</p><p><br></p><p><b>Needed Competencies:</b></p><p><br></p><p>● Fluent in both oral and written English</p><p>● Time Management skills</p><p>● Capable of succeeding in a very dynamic and fast-paced environment</p><p>● Able to work individually as well as being a cooperative team player</p><p>● Knowledge of programming languages</p><p>● Strong problem-solving skills</p><p>● Good attention to detail</p><p>● Excellent organisational and time management skills, and the ability to work on multiple projects at the same time</p><p>● Awareness of DevOps and Agile principles.</p><p><br></p><p><b>Knowledge, Skills and Abilities:</b></p><p><br></p><p>• Strong understanding of software development methodologies and the SDLC.</p><p>• Proficiency in scripting languages such as Bash, Python, or PowerShell.</p><p>• Experience with cloud platforms like AWS, Azure, or Google Cloud Platform.</p><p>• Knowledge of containerization technologies like Docker and container orchestration platforms like Kubernetes.</p><p>• Familiarity with infrastructure automation tools such as Terraform, Ansible, or CloudFormation.</p><p>• Experience with CI/CD tools like Jenkins, Travis CI, or GitLab CI/CD.</p><p>• Understanding of networking concepts and protocols.</p><p>• Knowledge of monitoring and logging tools such as Prometheus,New Relic Grafana, or ELK Stack.</p><p>• Strong problem-solving and troubleshooting skills.</p><p>• Excellent communication and collaboration skills.</p><p><br></p><p><b>Preferences:</b></p><p><br></p><p>● AWS Certified DevOps Engineer Professional.</p><p>● AWS Certified DevOps Engineer - Professional Certification.</p><p>● Azure DevOps Engineer Expert.</p><p>● Certified Kubernetes Administrator (CKA).</p><p>● Docker Certified Associate (DCA).</p><p>● Puppet Certified Professional.</p><p><br></p><p><b>Education:</b> Degree in Computer Science or related field (Master / Bachelor level).</p><p><br></p><p><b>Travel:</b> Based on customer requirement(s).</p><p><br></p><p><b>Work Schedule:</b> Local Avertra office schedule.</p><p><br></p><p>Benefits</p><p><b>What can we promise you:</b></p><ul><li>You’ll join a global family of awesome, passionate people that are working together to build a sustainable, scalable ecosystem committed to using logic to create a better experience.</li><li>We want you to help us become better. You will be empowered to drive change and innovate.</li><li>That we will invest in you. We will give you the opportunity to master your domain and drive excellence.</li></ul><p><br></p></div>
<p>1. JOB DETAILS:</p><p>Job Title: Analyst, ML Engineer</p><p>Reports to: Sr. Manager, IT Digital Platforms & 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 & 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 & 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 & 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 & 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 & 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 & 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 & Drive for Results - Very Good</p><p>Change & Innovation - Very Good</p><p>Communication & Influence - Good</p><p>Developing & Empowering others - Good</p><p>Problem Solving & decision Making - Excellent</p><p>Strategic Thinking - Good</p><p>6. Technical Competencies:</p><p>ML Model Development & Experimentation - Good</p><p>Python & ML Frameworks (PyTorch, TensorFlow, scikit-learn, HuggingFace) - Good</p><p>MLOps & Model Lifecycle Tooling - Good</p><p>Data Engineering & Pipeline Support - Good</p><p>Cloud AI/ML Services (Azure ML) - Good</p><p>Generative AI & LLM Development (RAG, LangChain, Semantic Kernel) - Very Good</p><p>Model Explainability & Responsible AI Awareness - Very Good</p><p>Containerization & CI/CD Basics (Docker, Git, Azure DevOps) - Good</p><p>7. COMMUNICATIONS & WORKING RELATIONSHIPS:</p><p>Internal: AI Champions Network, AI Architect, AI Developer, Data & Analytics Team</p><p>External: AI/ML Vendors & Solution Providers, Implementation Partners, Open Source & 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>
<p>GovCIO is currently hiring for an Information Assurance Engineer to participate with the client in the strategic design process to translate security and business requirements into technical designs. This position will be located in Jordan and will be fully onsite position.</p><p>Designs and implements information assurance and security engineering systems with requirements of business continuity, operations security, cryptography, forensics, regulatory compliance, internal counter-espionage (insider threat detection and mitigation), physical security analysis (including facilities analysis, and security management). Assesses and mitigates system security threats and risks throughout the program life cycle. Validates system security requirements definition and analysis. Establishes system security designs. Implements security designs in hardware, software, data, and procedures. Verifies security requirements; performs system certification and accreditation planning and testing and liaison activities. Supports secure systems operations and maintenance. Participates with the client in the strategic design process to translate security and business requirements into technical designs. Configures and validates secure systems and tests security products and systems to detect security weakness; performs network scanning and vulnerability analysis. Ensures that the appropriate security features and safeguards have been implemented on all information systems as required by DoD/IC policy and directives, and industry best practices. Performs defense device system installation, configuration maintenance, account maintenance, signature maintenance, patch management, and troubleshooting of all implemented, maintained, and deployed systems. Provides security certification test and evaluation of assets, vulnerability management and response, security assessments, customer support and provides guidance on security issues.</p><p><strong>Desired Candidate Profile</strong></p><ul><li>High School with 9+ years (or commensurate experience)</li><li>Clearance Required: TS/SCI</li><li>State-accredited Professional Engineer (PE) license through the National Council of Examiners for Engineering and Surveying (NCEES)</li></ul>
<p><h4>Description</h4>
<p>The forward deployed AI engineer will work directly with clients and senior engineers to build AI-powered systems inside real enterprise environments. This role is ideal for a strong junior engineer who wants to work on practical AI systems, enterprise data, agents, retrieval, workflow automation, and context graphs. You will help connect to client systems, process messy real-world data, build prototypes, and turn business problems into working software.</p>
<p>The work is hands-on and client-facing:</p>
<ul>
<li>Understand operational workflows and convert them into technical artifacts.</li>
<li>Connect to real enterprise systems and data sources.</li>
<li>Build context-aware AI agents, retrieval systems, and automation prototypes.</li>
<li>Help move the best prototypes toward reliable production deployments.</li>
</ul>
<h4>Requirements</h4>
<p>Build context graphs. Help ingest, clean, structure, and connect data from enterprise systems into context graphs. This may include structured databases, PDFs, spreadsheets, tickets, CRM data, analytics events, Slack or Teams exports, meeting transcripts, operational workflows, and other internal knowledge sources.</p>
<p>Develop AI and agentic workflows. Build AI pipelines and agent-based systems that can reason over enterprise context, identify patterns, surface workflow gaps, and suggest or trigger automations. This may involve LLMs, retrieval systems, structured extraction, tool use, LangGraph-style workflows, and agent harnesses.</p>
<p>Connect to enterprise systems. Integrate with client infrastructure such as databases, APIs, cloud storage, document repositories, analytics tools, ticketing systems, and internal applications.</p>
<p>Prototype automation opportunities. Rapidly build proof-of-concepts that show how AI can improve a client's operations – for example, process documentation, workflow discovery, incident management, document extraction, customer journey analysis, or operational decision support.</p>
<p>Turn messy business problems into software. Work with senior engineers and business stakeholders to translate ambiguous operational problems into technical designs, data models, prompts, pipelines, and deployed applications.</p>
<p>Support production deployments. Help build reliable, maintainable systems that can run in production environments, including client cloud environments when needed.</p>
<h4>Ideal candidate</h4>
<p>We are looking for a strong junior software engineer who is excited about applied AI and wants to build real systems, not just experiments.</p>
<p>You do not need to be an expert in every area below, but you should be curious, technical, and comfortable learning quickly.</p>
<h4>Technical background</h4>
<ul>
<li>Strong Python fundamentals.</li>
<li>Basic backend development experience.</li>
<li>Familiarity with APIs, databases, and cloud services.</li>
<li>Interest in LLMs, agents, retrieval, structured outputs, and tool-calling.</li>
<li>Familiarity with data pipelines and messy real-world datasets.</li>
<li>Experience with FastAPI, LangChain, LangGraph, vector databases, document processing, or knowledge graphs is a plus.</li>
<li>AWS experience is a plus.</li>
<li>Experience with enterprise data, analytics, or workflow automation is a strong plus.</li>
</ul>
<h4>What makes someone successful in this role</h4>
<ul>
<li>You like figuring out how businesses actually operate.</li>
<li>You are comfortable working with incomplete, messy, or poorly documented data.</li>
<li>You can move quickly from vague requirements to a working prototype.</li>
<li>You care about building useful systems, not just impressive demos.</li>
<li>You communicate clearly with both engineers and non-technical stakeholders.</li>
<li>You are curious about how AI agents can interact with real tools, data, and workflows.</li>
<li>You want to learn how to deploy AI into real enterprise environments.</li>
</ul>
<h4>Why this role is interesting</h4>
<p>You will work on the frontier of practical enterprise AI: connecting AI agents to real company context and using that context to discover and automate high-value workflows.</p>
<p>This is a hands-on engineering role for someone who wants to grow into building production-grade AI systems across data, agents, infrastructure, and enterprise software.</p></p><p></p>
<p><h4>Description</h4>
<p>The forward deployed AI engineer will work directly with clients and senior engineers to build AI-powered systems inside real enterprise environments. This role is ideal for a strong junior engineer who wants to work on practical AI systems, enterprise data, agents, retrieval, workflow automation, and context graphs. You will help connect to client systems, process messy real-world data, build prototypes, and turn business problems into working software.</p>
<p>The work is hands-on and client-facing:</p>
<ul>
<li>Understand operational workflows and convert them into technical artifacts.</li>
<li>Connect to real enterprise systems and data sources.</li>
<li>Build context-aware AI agents, retrieval systems, and automation prototypes.</li>
<li>Help move the best prototypes toward reliable production deployments.</li>
</ul>
<h4>Requirements</h4>
<p>Build context graphs. Help ingest, clean, structure, and connect data from enterprise systems into context graphs. This may include structured databases, PDFs, spreadsheets, tickets, CRM data, analytics events, Slack or Teams exports, meeting transcripts, operational workflows, and other internal knowledge sources.</p>
<p>Develop AI and agentic workflows. Build AI pipelines and agent-based systems that can reason over enterprise context, identify patterns, surface workflow gaps, and suggest or trigger automations. This may involve LLMs, retrieval systems, structured extraction, tool use, LangGraph-style workflows, and agent harnesses.</p>
<p>Connect to enterprise systems. Integrate with client infrastructure such as databases, APIs, cloud storage, document repositories, analytics tools, ticketing systems, and internal applications.</p>
<p>Prototype automation opportunities. Rapidly build proof-of-concepts that show how AI can improve a client's operations – for example, process documentation, workflow discovery, incident management, document extraction, customer journey analysis, or operational decision support.</p>
<p>Turn messy business problems into software. Work with senior engineers and business stakeholders to translate ambiguous operational problems into technical designs, data models, prompts, pipelines, and deployed applications.</p>
<p>Support production deployments. Help build reliable, maintainable systems that can run in production environments, including client cloud environments when needed.</p>
<h4>Ideal candidate</h4>
<p>We are looking for a strong junior software engineer who is excited about applied AI and wants to build real systems, not just experiments.</p>
<p>You do not need to be an expert in every area below, but you should be curious, technical, and comfortable learning quickly.</p>
<h4>Technical background</h4>
<ul>
<li>Strong Python fundamentals.</li>
<li>Basic backend development experience.</li>
<li>Familiarity with APIs, databases, and cloud services.</li>
<li>Interest in LLMs, agents, retrieval, structured outputs, and tool-calling.</li>
<li>Familiarity with data pipelines and messy real-world datasets.</li>
<li>Experience with FastAPI, LangChain, LangGraph, vector databases, document processing, or knowledge graphs is a plus.</li>
<li>AWS experience is a plus.</li>
<li>Experience with enterprise data, analytics, or workflow automation is a strong plus.</li>
</ul>
<h4>What makes someone successful in this role</h4>
<ul>
<li>You like figuring out how businesses actually operate.</li>
<li>You are comfortable working with incomplete, messy, or poorly documented data.</li>
<li>You can move quickly from vague requirements to a working prototype.</li>
<li>You care about building useful systems, not just impressive demos.</li>
<li>You communicate clearly with both engineers and non-technical stakeholders.</li>
<li>You are curious about how AI agents can interact with real tools, data, and workflows.</li>
<li>You want to learn how to deploy AI into real enterprise environments.</li>
</ul>
<h4>Why this role is interesting</h4>
<p>You will work on the frontier of practical enterprise AI: connecting AI agents to real company context and using that context to discover and automate high-value workflows.</p>
<p>This is a hands-on engineering role for someone who wants to grow into building production-grade AI systems across data, agents, infrastructure, and enterprise software.</p></p><p></p>
<p>We are seeking a talented Machine Learning Engineer to join our data science team. The ideal candidate will be responsible for developing and implementing machine learning models and algorithms that solve complex business problems. You will work closely with data scientists, software engineers, and stakeholders to deliver scalable solutions.</p><ul><li>Design, build, and deploy machine learning models and algorithms.</li><li>Collaborate with data scientists to refine data features and enhance model performance.</li><li>Optimize and improve existing machine learning models for efficiency and accuracy.</li><li>Conduct data preprocessing, feature engineering, and data analysis.</li><li>Monitor and maintain models in production to ensure they operate effectively.</li><li>Document and communicate model designs and performance metrics to stakeholders.</li><li>Stay updated on the latest industry trends and advancements in machine learning and AI.</li><li>Participate in code reviews and contribute to a culture of continuous improvement.</li><li>Perform statistical analysis, and train and retrain systems to optimize performance.</li><li>Familiarity with version control systems (e.g., Git) and CI/CD practices.</li><li>Experience with AI/GenAI.</li><li>Experience with AWS data services (e.g., AWS EMR, AWS Glue, AWS Athena).</li><li>Design/build and deploy API services.</li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li>Bachelor's degree in Computer Science, Data Science, Mathematics, or a related field.</li><li>Proven experience as a Machine Learning Engineer or in a similar role.</li><li>Proficiency in programming languages such as Python.</li><li>Experience with machine learning frameworks and libraries (e.g.,AWS BedRock, Amazon SageMaker, TensorFlow, PyTorch, Scikit-learn).</li><li>Strong understanding of algorithms, data structures, and software engineering principles.</li><li>Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and tools for deploying machine learning models.</li><li>Knowledge of data manipulation and analysis tools (e.g., SQL, Pandas, NumPy).</li><li>Excellent problem-solving skills and ability to work collaboratively in a team environment.</li><li>Experience with deep learning and natural language processing (NLP) techniques.</li><li>Understanding of model interpretability and explainability.</li></ul>
<p><h4>Description</h4>
<p>DeepSource Technologies is looking for a senior cloud infrastructure engineer specializing in Google Cloud Platform (GCP) to join our Riyadh, KSA team. In this senior role, you will design, implement, and manage scalable and secure cloud infrastructure solutions on GCP to support our dynamic business needs. You will collaborate closely with development, security, and operations teams to ensure high availability, performance, and cost-efficiency of cloud services.</p>
<h4>Key responsibilities:</h4>
<ul>
<li>Design and implement GCP-based infrastructure solutions including compute, storage, networking, and security services.</li>
<li>Manage and optimize cloud resources with a focus on performance, scalability, and cost.</li>
<li>Lead infrastructure automation initiatives using Infrastructure as Code (IaC) tools like Terraform and Deployment Manager.</li>
<li>Ensure compliance with security best practices and governance policies in cloud environments.</li>
<li>Monitor cloud infrastructure and troubleshoot issues to maintain high uptime and reliability.</li>
<li>Collaborate with DevOps and development teams to support CI/CD pipelines and cloud-native applications.</li>
<li>Stay up-to-date with latest GCP technologies and provide recommendations for cloud adoption and improvement.</li>
</ul>
<h4>Requirements</h4>
<ul>
<li>5+ years of experience in cloud infrastructure engineering, specifically with Google Cloud Platform.</li>
<li>Strong knowledge of GCP services such as Compute Engine, Kubernetes Engine, Cloud Storage, Cloud Networking, Cloud IAM, and BigQuery.</li>
<li>Experience with Infrastructure as Code tools like Terraform, Deployment Manager, or similar.</li>
<li>Proficient with containerization and orchestration technologies such as Docker and Kubernetes.</li>
<li>Strong understanding of networking, security, and compliance in cloud environments.</li>
<li>Experience with monitoring and logging tools such as Stackdriver, Prometheus, or Grafana.</li>
<li>Excellent troubleshooting and problem-solving skills.</li>
<li>Certification such as Google Cloud Professional Cloud Architect or Professional Cloud Engineer is preferred.</li>
<li>Good communication skills and ability to work in a dynamic team environment.</li>
</ul>
<h4>Benefits</h4>
<p>This is a 3-month, full-time onsite engagement offering a premium experience for the right consultant:</p>
<ul>
<li>Global mobility: full coverage of visa costs and airline tickets (round trip).</li>
<li>Medical insurance.</li>
</ul></p><p></p>
<p><h4>Description</h4>
<p>DeepSource Technologies is looking for a senior cloud infrastructure engineer specializing in Google Cloud Platform (GCP) to join our Riyadh, KSA team. In this senior role, you will design, implement, and manage scalable and secure cloud infrastructure solutions on GCP to support our dynamic business needs. You will collaborate closely with development, security, and operations teams to ensure high availability, performance, and cost-efficiency of cloud services.</p>
<h4>Key responsibilities:</h4>
<ul>
<li>Design and implement GCP-based infrastructure solutions including compute, storage, networking, and security services.</li>
<li>Manage and optimize cloud resources with a focus on performance, scalability, and cost.</li>
<li>Lead infrastructure automation initiatives using Infrastructure as Code (IaC) tools like Terraform and Deployment Manager.</li>
<li>Ensure compliance with security best practices and governance policies in cloud environments.</li>
<li>Monitor cloud infrastructure and troubleshoot issues to maintain high uptime and reliability.</li>
<li>Collaborate with DevOps and development teams to support CI/CD pipelines and cloud-native applications.</li>
<li>Stay up-to-date with latest GCP technologies and provide recommendations for cloud adoption and improvement.</li>
</ul>
<h4>Requirements</h4>
<ul>
<li>5+ years of experience in cloud infrastructure engineering, specifically with Google Cloud Platform.</li>
<li>Strong knowledge of GCP services such as Compute Engine, Kubernetes Engine, Cloud Storage, Cloud Networking, Cloud IAM, and BigQuery.</li>
<li>Experience with Infrastructure as Code tools like Terraform, Deployment Manager, or similar.</li>
<li>Proficient with containerization and orchestration technologies such as Docker and Kubernetes.</li>
<li>Strong understanding of networking, security, and compliance in cloud environments.</li>
<li>Experience with monitoring and logging tools such as Stackdriver, Prometheus, or Grafana.</li>
<li>Excellent troubleshooting and problem-solving skills.</li>
<li>Certification such as Google Cloud Professional Cloud Architect or Professional Cloud Engineer is preferred.</li>
<li>Good communication skills and ability to work in a dynamic team environment.</li>
</ul>
<h4>Benefits</h4>
<p>This is a 3-month, full-time onsite engagement offering a premium experience for the right consultant:</p>
<ul>
<li>Global mobility: full coverage of visa costs and airline tickets (round trip).</li>
<li>Medical insurance.</li>
</ul></p><p></p>
<section><p class="heading jdMain">Job Description</p><p class="heading">Roles & Responsibilities</p><div class="paragraph"><p>A leading global pharmaceutical company is seeking an experienced Data Engineer / BI Engineer to design, build, and maintain scalable data platforms that enable analytics, reporting, and data-driven decision making. The role focuses on data ingestion, transformation, modeling, and analytics enablement, with strong emphasis on Python-based data engineering and modern data architectures.</p><p>Responsibilities:</p><p>1. Data Engineering & Data Architecture: Design and maintain scalable data pipelines for ingesting, transforming, and serving structured and semi-structured data. Develop robust data transformation and processing logic using Python and distributed data processing frameworks. Design and maintain analytical data models (dimensional models, fact/dimension tables) optimized for reporting and analytics. Ensure data quality, reliability, performance, and consistency across the data platform. Translate business and analytical requirements into efficient and maintainable data solutions.</p><p>2. Analytics & BI Enablement: Build and maintain semantic / analytical models that support enterprise reporting and self-service analytics. Collaborate with analysts and business users to deliver trusted datasets and metrics. Support reporting and dashboarding solutions by providing optimized data structures and calculations.</p><p>3. Delivery & Collaboration: Produce clear technical documentation including data models, transformation logic, and pipeline designs. Collaborate with cross-functional teams including data analysts, data engineers, and business stakeholders.</p><p>Bachelor s degree in data science, computer science, data engineering, or a relevant field.</p><p>1-3 years of BI development experience.</p><p>3+ years of cloud-based BI development experience</p><p>Excellent English language verbal and written communication.</p><p>Able to analyse and understand complex data.</p><p>Able to implement modules that have security and authorization frameworks.</p><p>Strong problem-solving skills</p><p>Technical Skills:</p><p>Programming & Data Processing: Strong proficiency in Python for data engineering and analytics use cases. Experience building reusable, testable, and maintainable data transformation code.</p><p>Data Warehousing & Modeling: Strong knowledge of SQL and analytical query optimization. Solid understanding of data warehousing concepts (ETL/ELT, fact and dimension modeling). Experience designing star and snowflake schemas for analytics and reporting. Understanding of semantic layers and metrics definitions for BI consumption.</p><p>Cloud & Modern Data Platforms: Experience working with cloud-based data platforms and data lakes(Preferred Azure). Understanding of scalable data architectures (Lakehouse, warehouse, streaming vs batch).</p><p>BI & Analytics: Experience supporting BI and reporting tools through well-designed datasets and models (Preferred Power BI). Knowledge of analytical calculations, KPIs, and performance optimization for reporting workloads.</p><p>CI/CD & DevOps (Supporting Skills): Working knowledge of CI/CD concepts applied to data and analytics projects. Experience using version control systems (e.g., Git, Perforce or Apache Subversion) for managing data, code, and artifacts. Familiarity with deployment pipelines and environment promotion for data solutions'</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p>Bachelor s degree in data science, computer science, data engineering, or a relevant field.</p><p>1-3 years of BI development experience.</p><p>3+ years of cloud-based BI development experience</p><p>Excellent English language verbal and written communication.</p><p>Able to analyse and understand complex data.</p><p>Able to implement modules that have security and authorization frameworks.</p><p>Strong problem-solving skills</p><p>Technical Skills:</p><p>Programming & Data Processing: Strong proficiency in Python for data engineering and analytics use cases. Experience building reusable, testable, and maintainable data transformation code.</p><p>Data Warehousing & Modeling: Strong knowledge of SQL and analytical query optimization. Solid understanding of data warehousing concepts (ETL/ELT, fact and dimension modeling). Experience designing star and snowflake schemas for analytics and reporting. Understanding of semantic layers and metrics definitions for BI consumption.</p><p>Cloud & Modern Data Platforms: Experience working with cloud-based data platforms and data lakes(Preferred Azure). Understanding of scalable data architectures (Lakehouse, warehouse, streaming vs batch).</p><p>BI & Analytics: Experience supporting BI and reporting tools through well-designed datasets and models (Preferred Power BI). Knowledge of analytical calculations, KPIs, and performance optimization for reporting workloads.</p><p>CI/CD & DevOps (Supporting Skills): Working knowledge of CI/CD concepts applied to data and analytics projects. Experience using version control systems (e.g., Git, Perforce or Apache Subversion) for managing data, code, and artifacts. Familiarity with deployment pipelines and environment promotion for data solutions'</p><p></p></section>
<p>We believe in bold ideas, diverse perspectives, and the drive to transform knowledge into impact. Here, your curiosity fuels progress, your voice shapes innovation, and your ambition helps redefine what s possible within science and learning. We are a culture that obsesses over impact, challenges, and drives what s next to power infinite possibilities for our customers, colleagues and society at large.</p><p>About the Role:</p><p>The Senior Software Engineer transforms high-level architecture into detailed technical solutions while building scalable, high-performing applications that enhance customer learning and engagement experiences. Operating across critical areas of the technology stack, this role is responsible for designing, developing, testing, and releasing software solutions that deliver business value and exceptional customer outcomes. Working independently with minimal guidance, the Senior Software Engineer takes ownership of services, systems, and technical responsibilities, applying a full-stack, full-lifecycle approach to software delivery. This role also provides technical leadership, mentors team members, and contributes to the continuous improvement of engineering practices and technologies.</p><p>How You Will Make an Impact</p><p>Application Design & Development</p><ul><li>Design, develop, and release scalable applications and systems that improve customer learning and engagement experiences.</li><li>Translate high-level architectural concepts into detailed technical designs that are clearly understood and implemented by development teams.</li><li>Build robust, maintainable software solutions that support business objectives and customer needs.</li></ul><p>Technical Leadership</p><ul><li>Serve as a technical leader within the engineering team, providing guidance on design decisions, architecture, and development best practices.</li><li>Mentor and coach junior engineers, helping to elevate technical capabilities across the team.</li><li>Drive technical excellence through knowledge sharing, collaboration, and continuous improvement initiatives.</li></ul><p>System Ownership & Delivery</p><ul><li>Take ownership of services and systems throughout the entire software development lifecycle.</li><li>Partner with cross-functional teams to design, build, deploy, monitor, and support solutions in production environments.</li><li>Evaluate, recommend, and implement technologies that improve scalability, reliability, and maintainability.</li></ul><p>Code Quality & Engineering Excellence</p><ul><li>Establish and maintain code repository structures, branching strategies, and development standards.</li><li>Conduct thorough code reviews and champion clean, maintainable, and high-quality code.</li><li>Promote engineering best practices including test-driven development, automated testing, continuous integration, and continuous deployment.</li></ul><p>Cross-Functional Collaboration</p><ul><li>Collaborate closely with Product, Data Engineering, Data Science, Site Reliability Engineering (SRE), and other specialized teams.</li><li>Contribute effectively within multidisciplinary Agile teams to deliver business and customer value.</li><li>Communicate technical concepts clearly to both technical and non-technical stakeholders.</li></ul><p>Innovation & Continuous Improvement</p><ul><li>Drive innovation by exploring and implementing new tools, technologies, and engineering approaches.</li><li>Lead technical initiatives that improve platform performance, scalability, and customer experience.</li><li>Contribute to strategic technology decisions that support long-term business objectives.</li></ul><p><strong>Desired Candidate Profile</strong></p><h2>What We Look For</h2><p>Required Qualifications</p><ul><li>Bachelor's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.</li><li>6+ years of professional software development experience.</li><li>Proven experience serving as a technical lead or senior engineer within a software engineering team.</li><li>Strong proficiency in C#/.NET development.</li><li>Expert understanding of object-oriented design principles, software architecture, and system design.</li><li>Experience building and consuming web APIs and microservices-based architectures.</li><li>Experience working with cloud-based services and containerization technologies such as Docker.</li><li>Strong knowledge of relational and/or non-relational database technologies.</li><li>Experience with Agile software development methodologies and DevOps practices.</li><li>Hands-on experience with continuous integration and continuous deployment (CI/CD) pipelines.</li><li>Experience with automated testing and test-driven development (TDD).</li><li>Excellent written and verbal communication skills.</li><li>Demonstrated ability to work independently while collaborating effectively within cross-functional teams.</li></ul><p>Preferred Qualifications</p><ul><li>Experience working within multidisciplinary product and engineering organizations.</li><li>Knowledge of modern cloud-native application architectures.</li><li>Experience supporting large-scale, customer-facing applications.</li><li>Track record of successfully leading technical initiatives and driving engineering innovation.</li><li>Passion for mentoring and developing engineering talent</li></ul>
<p>Job Description We are seeking a talented and motivated Senior Mechanical Engineer to join our team in Amman, Jordan. In this role, you will take the lead on mechanical engineering design tasks, deliver high-quality technical solutions, mentor junior engineers, and collaborate closely with multidisciplinary teams to ensure the successful delivery of engineering projects. This is a key technical delivery role for an engineer ready to work with a high degree of independence and take ownership of design outcomes. Key Responsibilities Lead and deliver the mechanical design of projects from concept through detailed design and construction support. Implement mechanical engineering methodologies, standards, and best practices across assigned projects. Perform and check engineering calculations, technical analyses, and system evaluations to optimize performance, reliability, and cost-effectiveness. Prepare, review, and coordinate mechanical design drawings, specifications, schedules, and technical reports. Collaborate with multidisciplinary teams to develop integrated solutions and resolve design interfaces. Ensure all designs comply with applicable codes, standards, client requirements, and company quality procedures. Identify technical issues, evaluate alternatives, and develop practical, innovative engineering solutions. Support project planning activities and monitor progress against schedules, deliverables, and quality standards. Coordinate with clients, contractors, vendors, and project stakeholders as required. Provide technical guidance, mentoring, and support to graduate and junior engineers. Participate in design reviews, value engineering studies, and quality assurance/quality control processes. Contribute to continuous improvement initiatives and knowledge-sharing within the engineering team. Stay current with industry trends, emerging technologies, sustainability practices, and digital engineering tools.</p><p><strong>Desired Candidate Profile</strong></p><p>Qualifications Bachelor's Degree in Mechanical Engineering (Master's degree an advantage). 6 8 years of relevant mechanical engineering experience, with demonstrated ability to lead the mechanical design of projects independently and coordinate across disciplines. Sound working knowledge of relevant international codes and standards. Proven experience in the design and delivery of multidisciplinary engineering projects. Strong analytical, technical, and problem-solving skills. Excellent communication, coordination, and teamwork abilities. Proficiency in industry-standard engineering and design software. Professional registration or working towards chartership/professional membership is an advantage.</p>
<p><b>Sr. Product Engineer</b></p><p><br></p><p>Lead technical initiatives and mentor the engineering team. Own key systems end-to-end and drive architectural decisions.</p>
<p><b>Product Engineer</b></p><p><br></p><p>Build and ship features that help thousands of salons run their business. Work across the full stack with a small, fast-moving team.</p>
<h2 class="h5">Job description</h2>
<div class="t-break" data-jb-field="description">
<span>We are looking for Expert Storage Administrators with strong hands-on experience managing S3 and NFS storage platforms within high-performance computing (HPC) environments.<br> The role is responsible for ensuring high availability, performance, scalability, capacity, and secure data access across storage infrastructure.<br> Key Responsibilities Administer, configure, and support S3 and NFS storage platforms .<br> Monitor and optimize storage performance, capacity, availability, and scalability .<br> Manage storage access, permissions, quotas, replication, and data protection .<br> Troubleshoot storage, filesystem, and data-access issues across HPC environments.<br> Support storage integration with Linux, Kubernetes, and HPC workloads .<br> Perform storage health monitoring, performance analysis, and capacity planning.<br> Support data replication, backup, recovery, and protection mechanisms.<br> Automate routine storage administration and maintenance activities where applicable.<br> Participate in incident resolution and root-cause analysis for storage-related issues.<br> Maintain technical documentation, configurations, and operational procedures.<br> Strong hands-on experience as a Storage Administrator / Storage Engineer .<br> Expert-level S3 and NFS administration is mandatory.<br> Experience supporting HPC storage environments .<br> Strong knowledge of Linux storage and filesystem administration .<br> Experience integrating storage with Kubernetes/containerized workloads .<br> Strong understanding of: S3 / Object Storage NFS Storage performance & monitoring Capacity management Permissions & access control Quotas Replication Data protection High availability Experience troubleshooting complex storage and data-access issues .<br> Experience with storage automation/scripting is preferred.<br> Relevant storage certifications are preferred.<br></span> </div>
<p><h4>Description</h4>
<p>We are looking for a sales engineer - cybersecurity services to join our managed services team and support the growth and delivery of our cybersecurity solutions.</p>
<p>As a sales engineer, you will act as a technical expert and trusted advisor to our sales team and clients, helping to identify cybersecurity needs and tailor solutions that address complex security challenges.</p>
<p>This role requires strong technical knowledge of cybersecurity products and services, combined with excellent communication and interpersonal skills to effectively articulate technical concepts to both technical and non-technical stakeholders.</p>
<h4>Key responsibilities</h4>
<ul>
<li>Collaborate with sales, engineering, and operations teams to develop and present tailored cybersecurity service solutions.</li>
<li>Engage with prospective and existing clients to understand their security requirements and challenges.</li>
<li>Deliver technical presentations, demonstrations, and proof of concepts to articulate the value of our cybersecurity services.</li>
<li>Assist in the development of proposals, statements of work, and project scoping.</li>
<li>Provide technical support throughout the sales cycle, including responding to RFPs and RFIs.</li>
<li>Stay current with cybersecurity trends, technologies, and industry regulations to inform sales strategies.</li>
<li>Support marketing and business development initiatives by providing technical insights and content.</li>
</ul>
<h4>Requirements</h4>
<ul>
<li>Bachelor’s degree in cybersecurity, computer science, engineering, or a related field.</li>
<li>3+ years of experience in cybersecurity solutions, consulting, or technical sales engineering.</li>
<li>Strong understanding of cybersecurity technologies, including network security, threat detection, identity and access management, and compliance standards.</li>
<li>Excellent communication and presentation skills, with the ability to translate technical information for diverse audiences.</li>
<li>Experience collaborating with sales teams and managing client relationships.</li>
<li>Ability to handle multiple projects and prioritize tasks in a fast-paced environment.</li>
<li>Willingness to travel as needed to meet with clients and attend industry events.</li>
</ul>
<h4>Preferred qualifications</h4>
<ul>
<li>Certifications such as CISSP, CISA, or sales engineering credentials.</li>
<li>Knowledge of cloud security platforms and managed security services.</li>
<li>Familiarity with cybersecurity frameworks like NIST, ISO 27001, or CSA CCM.</li>
<li>Experience working in managed services or consulting environments.</li>
</ul>
<h4>Benefits</h4>
<ul>
<li>Opportunity to work with a leading cybersecurity services company.</li>
<li>Exposure to major cybersecurity governance and compliance projects in KSA.</li>
<li>Remote work from Jordan.</li>
<li>Professional growth in cybersecurity consulting, risk, and compliance.</li>
<li>Collaborative and expert-driven work environment.</li>
</ul></p><p></p>
<p><h4>Description</h4>
<p>We are looking for a sales engineer - cybersecurity services to join our managed services team and support the growth and delivery of our cybersecurity solutions.</p>
<p>As a sales engineer, you will act as a technical expert and trusted advisor to our sales team and clients, helping to identify cybersecurity needs and tailor solutions that address complex security challenges.</p>
<p>This role requires strong technical knowledge of cybersecurity products and services, combined with excellent communication and interpersonal skills to effectively articulate technical concepts to both technical and non-technical stakeholders.</p>
<h4>Key responsibilities</h4>
<ul>
<li>Collaborate with sales, engineering, and operations teams to develop and present tailored cybersecurity service solutions.</li>
<li>Engage with prospective and existing clients to understand their security requirements and challenges.</li>
<li>Deliver technical presentations, demonstrations, and proof of concepts to articulate the value of our cybersecurity services.</li>
<li>Assist in the development of proposals, statements of work, and project scoping.</li>
<li>Provide technical support throughout the sales cycle, including responding to RFPs and RFIs.</li>
<li>Stay current with cybersecurity trends, technologies, and industry regulations to inform sales strategies.</li>
<li>Support marketing and business development initiatives by providing technical insights and content.</li>
</ul>
<h4>Requirements</h4>
<ul>
<li>Bachelor’s degree in cybersecurity, computer science, engineering, or a related field.</li>
<li>3+ years of experience in cybersecurity solutions, consulting, or technical sales engineering.</li>
<li>Strong understanding of cybersecurity technologies, including network security, threat detection, identity and access management, and compliance standards.</li>
<li>Excellent communication and presentation skills, with the ability to translate technical information for diverse audiences.</li>
<li>Experience collaborating with sales teams and managing client relationships.</li>
<li>Ability to handle multiple projects and prioritize tasks in a fast-paced environment.</li>
<li>Willingness to travel as needed to meet with clients and attend industry events.</li>
</ul>
<h4>Preferred qualifications</h4>
<ul>
<li>Certifications such as CISSP, CISA, or sales engineering credentials.</li>
<li>Knowledge of cloud security platforms and managed security services.</li>
<li>Familiarity with cybersecurity frameworks like NIST, ISO 27001, or CSA CCM.</li>
<li>Experience working in managed services or consulting environments.</li>
</ul>
<h4>Benefits</h4>
<ul>
<li>Opportunity to work with a leading cybersecurity services company.</li>
<li>Exposure to major cybersecurity governance and compliance projects in KSA.</li>
<li>Remote work from Jordan.</li>
<li>Professional growth in cybersecurity consulting, risk, and compliance.</li>
<li>Collaborative and expert-driven work environment.</li>
</ul></p><p></p>
<h2 class="h5">Job description</h2>
<div class="t-break" data-jb-field="description">
<span>Who are we?<br> We are a team of driven individuals who strongly believe in the positive impact gaming and AI will have on the learning world.<br> Today, we’re helping enterprise businesses transition from video to gamified learning experiences that far outperform their traditional counterparts.<br> If you strive to work in a creative and high-output environment, read on.<br> Who are we looking for?<br> A senior data engineer to own Pixaera's data end to end: the pipelines that bring data in, the warehouse and transformations that shape it, and the customer-facing dashboards and insights we build on top.<br> Our customers judge the value of their training by what they can see, so this role owns that surface directly.<br> Today the stack is Fivetran into Snowflake, transformed with dbt and surfaced through Omni.<br> You will take real ownership of it, fix what is brittle, and turn it into a genuine product surface rather than a side project.<br> You are happy working across the backend to solve data problems at their source, and you can explain a trade-off to a customer success lead as clearly as to an engineer.<br> What you will own Customer-facing dashboards and reporting: the activity, completion and performance views customers rely on, built on the current data model (courses and completions, not legacy sessions) and kept correct as new content ships.<br> The data platform end to end: ingestion (Fivetran), the warehouse and data lake (Snowflake) and the transformation layer (dbt), including the modelling that harmonises sources and versions data properly.<br> Turning raw learning and assessment data into insights that customers and internal teams can act on, and moving us toward live and near-real-time reporting.<br> Reliability and cost: monitored, well-behaved pipelines, sensible incremental versus full-refresh models, and a real handle on data spend.<br> Data products beyond dashboards: APIs, reports and exports, and the content mappings that keep reporting accurate, owned inside the publish pipeline rather than as manual handoffs.<br> The data layer in product design: partnering with backend and frontend engineers so new features integrate with data cleanly from the start, and raising the bar for data practice across engineering.<br> How do we support and benefit our employees: Competitive salary and stock options — everyone shares in what we're building 25 days holiday + public holidays Fully equipped setup from day one (no waiting for laptops) Regular company offsites and team socials A flat, transparent culture with direct access to leadership At Pixaera, we're committed to building a workplace where everyone feels respected, supported, and empowered to thrive.<br> We believe that diverse perspectives fuel creativity and innovation, which is why we celebrate individuality and foster an environment of inclusion and belonging.<br> We're proud to be an equal opportunity employer — discrimination of any kind has no place here.<br> No matter your background, identity, or lived experience, you're welcome at Pixaera.<br> Skills / Experiences Core Significant professional experience as a Data Engineer , senior enough to own a platform and its customer-facing outputs on your own.<br> Proven ability to independently master new concepts and technologies.<br> Strong skills in analysing business processes and modelling data for reporting.<br> Proven ability to communicate complex technical concepts and trade-offs to non-technical audiences.<br> Excellent written and spoken English.<br> Self-motivated, independent and proactive; able to thrive in a fully remote environment.<br> AI-native: fluent with agentic coding tools such as Claude Code on real deliverables, and keen to build AI and agentic steps into data pipelines and tooling.<br> Data tech Strong proficiency in writing Python and SQL.<br> Strong grounding in data structures, algorithms, and system design.<br> Proficiency with data warehousing tools like Snowflake and data transformation tools like dbt.<br> Comfortable modelling and delivering customer-facing dashboards in a BI tool such as Omni , Looker, Metabase or similar.<br> General tech Solid software engineering practices: testing, code review, CI/CD.<br> Experience deploying data solutions to production environments .<br> Experience with performance optimization and cost control in data pipelines.<br> Experience with one or more public clouds (like AWS, Google Cloud, Azure).<br> Nice to Have Experience with Omni specifically, or migrating between BI tools.<br> Backend fluency (Golang, NodeJS, Postgres) to fix data issues at their source.<br> Setting up and prototyping solutions using AWS; Kubernetes.<br> Experience working at or with education and/or assessment solutions.<br></span> </div>
<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>
<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>Job Summary: We are seeking an experienced SIEM Deployment Engineer to lead or support the deployment, configuration, and optimization of Splunk or SIEM solutions across enterprise environments.<br> The ideal candidate will possess strong technical knowledge in security operations, log management, and compliance, along with hands-on experience in implementing for clients.<br> Key Responsibilities: Lead end-to-end deployment of Splunk or SIEM platform, including planning, architecture design, installation, configuration, and tuning.<br> Integrate log sources from various platforms (Windows, Linux, firewalls, routers, endpoint protection, etc.<br>). Develop custom parsers and log normalization rules.<br> Build correlation rules, alerts, dashboards, and reports based on customer requirements.<br> Conduct use case development, threat detection tuning, and optimization of false positives.<br> Collaborate with SOC teams to ensure effective threat monitoring and incident detection.<br> Document implementation procedures, configuration guides, and troubleshooting steps.<br> Provide knowledge transfer and training to internal teams or clients.<br> Ensure compliance with industry standards (e.<br>g., NCA ECC, SAMA CSF, ISO 27001).<br> Required Skills and Qualifications: Bachelor’s degree in Computer Science, Cybersecurity, or related field.<br> 8-10 years of experience in Splunk or SIEM deployment and cybersecurity.<br> Proven experience with LogRhythm SIEM deployment in enterprise environments.<br> Strong understanding of log analysis, incident response, and threat detection.<br> Familiarity with log source integration: Windows Event Logs, Syslog, NetFlow, etc.<br> Scripting experience (PowerShell, Python, etc.<br>) is a plus.<br> Knowledge of cybersecurity frameworks (MITRE ATT&CK, NIST, etc.<br>) is an advantage.<br> LogRhythm certifications (e.<br>g., LogRhythm Deployment Fundamentals, LogRhythm Analyst) are a strong plus.<br></span> </div>