AI Technical Lead/AI Solution Architect

Company not disclosed

Dubai, United Arab Emirates
Salary not specified
Posted
Full-time
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Job Description

We are seeking an experienced AI Technical Lead / AI Solution Architect to design and deliver production-grade AI/ML solutions within a government or highly regulated environment. The role combines hands-on AI engineering, solution architecture, Generative AI expertise and technical leadership. The successful candidate will define technical solutions, guide implementation, review architecture and code, and technically lead AI delivery teams. Key Requirements - Proven hands-on experience designing and delivering AI/ML solutions into production. - Strong practical knowledge of Machine Learning, Generative AI/LLMs and Agentic AI. - Strong Python development skills, with the ability to prototype, review and guide production AI/ML implementations. - Practical experience with RAG, embeddings, vector search, prompt engineering, tool/function calling, agent orchestration and LLM evaluation. - Strong AI solution architecture and integration capabilities, including scalability, security, reliability, performance and cost considerations. - Experience designing AI solutions across public cloud, hybrid, private or sovereign cloud environments. - Strong Microsoft Azure experience, ideally including Azure OpenAI, Azure AI Foundry, Azure AI Search and Azure Machine Learning. - Understanding of MLOps/LLMOps, including deployment, evaluation, monitoring, versioning and production lifecycle management. - Strong understanding of AI security, governance, responsible AI, data privacy and data sovereignty. - Experience with modern software engineering practices including APIs, microservices, containers, Kubernetes and CI/CD. - Proven experience technically leading and mentoring AI Developers, ML Engineers and Data Scientists. Technical Stack Experience with relevant technologies across: - GenAI/LLM: Azure OpenAI, Azure AI Foundry, OpenAI-compatible APIs, Hugging Face or equivalent. - RAG & Search: Azure AI Search, vector databases, embeddings and semantic search. - Agentic AI: LangChain, LangGraph, Semantic Kernel, LlamaIndex or equivalent agent frameworks. - ML/MLOps: Azure Machine Learning, MLflow or equivalent. - Cloud & Engineering: Microsoft Azure, REST APIs, microservices, Docker, Kubernetes, Git and CI/CD. - Data: SQL/NoSQL, data pipelines, data lakes/lakehouses; Databricks, Spark or Microsoft Fabric are advantageous. Depth of technical capability is more important than experience with every named technology. Preferred Experience - Government or highly regulated environments. - Experience with data residency, sovereignty, security and regulatory requirements. - AI governance, cybersecurity and responsible AI. - Production MLOps / LLMOps. - Computer Vision. - High-volume, scalable or real-time AI solutions. - Open-source or self-hosted LLMs. - Hybrid, private or sovereign cloud architectures.

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