AI Technical Lead/AI Solution Architect
- غير محدد
نُشرت أول أمس
عن الوظيفة
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.