AI Engineer - Senior

Role Summary

AI only earns trust in government when it is accurate, explainable and secure. The Senior AI Engineer leads the design, build and deployment of production-grade AI and GenAI solutions on governed, high-quality data. They own the technical architecture and quality of AI solutions end to end, turning complex use cases into reliable applications that are measurable, auditable and compliant with UAE AI and data regulation.

The role works alongside business analysts, data architects, data engineers and the Data Governance Council, and acts as the technical lead and mentor for junior AI engineers. Its job is to take AI from prototype to production at scale, using the Microsoft Azure AI ecosystem on top of the Purview-governed data foundation, and to set the engineering and responsible-AI standards the team follows.

Key Responsibilities

• Lead the end-to-end design, development and deployment of AI/ML and GenAI applications, including RAG assistants, document intelligence, classification, prediction and Arabic/English NLP use cases, from use-case shaping through to production operations.
• Architect enterprise-scale retrieval-augmented generation solutions using Azure OpenAI / Azure AI Foundry, Azure AI Search, vector indexing, hybrid retrieval and re-ranking, agentic and prompt orchestration, and grounding on curated Gold-layer data, optimising for accuracy, latency and cost.
• Define and operationalise responsible-AI controls covering explainability, bias testing, content safety, hallucination controls and human-in-the-loop review, aligned to the UAE Charter for the Development and Use of AI and Dubai's AI ethics principles, and present them to the Data Governance Council.
• Design secure, scalable APIs and integration patterns that connect AI capabilities with enterprise applications, portals and analytics, with role-based access, data masking, private networking and identity controls enforced.
• Partner with data architects and data engineers to define AI-ready data products, feature pipelines and data-quality gates, and ensure training and grounding data meets DQ and classification controls.
• Establish the evaluation framework: accuracy, relevance, latency and cost KPIs, automated regression testing, red-teaming and go/no-go release criteria applied before each release.
• Own CI/CD, model and prompt versioning, monitoring, drift detection, observability and cost management for AI workloads in production.
• Lead the application of UAE PDPL, Dubai Data Law and DESC ISR requirements to AI workloads, including threat modelling, data residency, PII handling and prompt/response logging, in coordination with security and data-protection teams.
• Act as technical lead for the AI workstream: lead and mentor junior AI engineers, run design and code reviews, set engineering standards and best practices, and support estimation, planning and delivery quality.
• Advise senior business and technology stakeholders on AI feasibility, risk, roadmap and trade-offs, and translate business needs into clear technical solutions and delivery plans.
• Produce and review model cards, solution architecture and design decisions, runbooks and audit evidence for each AI component.
• Lead capability building for Client's counterparts in AI engineering practices, tooling and responsible-AI operations so that solutions can be sustained after handover.

• AI certification.
• 8+ years in software engineering, with at least 4 years designing, building and deploying AI/ML or GenAI solutions in production, including ownership of multiple enterprise-scale deployments.
• Proven experience as a technical lead, guiding and mentoring a team of engineers and owning solution architecture and delivery quality.
• Expert-level Python skills, with deep experience in frameworks such as LangChain, Semantic Kernel, PyTorch, scikit-learn or Hugging Face, and in building agentic and multi-step LLM workflows.
• Deep hands-on experience with Azure OpenAI / Azure AI Foundry, Azure AI Search, Azure Machine Learning and vector databases, including hybrid retrieval, evaluation and fine-tuning approaches.
• Strong experience designing scalable APIs and services (REST/FastAPI), containerization (Docker/Kubernetes), CI/CD pipelines and infrastructure as code.
• Strong command of MLOps/LLMOps, model evaluation, prompt engineering, red-teaming, observability and responsible-AI practices.
• Solid understanding of lakehouse architecture, Microsoft Fabric and governed data consumption through Purview.
• Working knowledge of UAE AI and data regulation, including the UAE AI Charter, UAE PDPL, the Dubai Data Law and DESC ISR, with experience applying it in delivery.
• Excellent English communication, documentation and stakeholder-management skills.

• Arabic proficiency and Arabic NLP experience.
• Relevant Microsoft Azure AI or architecture certifications (for example Azure AI Engineer Associate or Azure Solutions Architect Expert).
• Experience in government or other regulated sectors.