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Cognitive

AI Technical Lead/AI Solution Architect

  • Not specified

Posted 2 days ago

About the role

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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