About the job

Principal Azure AI EngineerContract (6 to 12 months) or Permanent - Open to bothDublin, hybrid (3 days on site)

Microsoft / Azure AI stack . .. PYTHON - Infrastructure-as-Code . . . . RBAC - RAG . . . We are seeking a Principal Azure AI Engineer , with Microsoft / Azure Stack expertise, to build out enterprise AI capability. We need a candidate who can demonstrate that they have built and shipped AI on the Microsoft stack, so deep hands-on Azure experience is important. It is a hybrid architecture and engineering role, which means you will shape the solution and write the code that delivers it.

So while AWS or GCP experience is welcome we really need to see candidates with experience shaped around Azure. This is a build role, so production delivery is what this role is all about.

1. What the role needs:Proven, hands-on delivery of AI into production on Azure.
2. Can demonstrate that you have delivered real solutions ( not proofs of concept, or theory or consulting) but execution and accountability.
3. Deep, current Azure AI experience: Azure OpenAI and AI Foundry, Azure AI Search, and Azure AI Document Intelligence, with App Services, Functions and API Management.
4. Secure-by-design on Azure: Entra ID and managed identity, RBAC, Key Vault, private endpoints and restricted public access.
5. Building RAG systems that pull the right information from large document sets and keep the AI's answers accurate and grounded, with the retrieval quality tested rather than assumed.
6. Experience building AI agents that carry out multi-step tasks reliably, calling other tools and systems, handling errors and returning results in a consistent, usable format. Familiarity with frameworks such as Semantic Kernel, LangGraph or LangChain.
7. Strong hands-on Python, Infrastructure-as-Code with Bicep, and LLMOps: tracing, cost and latency monitoring, groundedness and regression testing.
8. Enterprise integration across Microsoft 365, SharePoint, Microsoft Graph, Power Automate and Logic Apps.
9. AI governance and data residency: EU AI Act and EU Data Boundary, model lifecycle and approved model catalogues.

Also useful:1. The ability to stand up a React or TypeScript UI over your own APIs.2. Vector database experience and relevant Azure certifications.

There is also scope for a permanent or contract-to-permanent arrangement for the right person.

If this is you and you want to hear more please email Fergal Keys for more information on Fergalk@thepanel.com

·        Generative AI and LLM Engineering: LLM Application Development, Retrieval Augmented Generation (RAG), Prompt Engineering, LangChain, LangGraph, AI Agents, Multi Agent Systems, Model Context Protocol (MCP), Hugging Face Transformers, OpenAI GPT, Anthropic Claude, Google Gemini, Meta Llama, Groq

·        Vector Search and Data Engineering: ChromaDB, FAISS, Pinecone, Sentence Transformers, Semantic Search, Python, SQL, PostgreSQL, Pydantic

·        Machine Learning and Deployment: Deep Learning, TensorFlow, PyTorch, Natural Language Processing, Computer Vision, FastAPI, SQLAlchemy, Alembic, Docker, Docker Compose, MLOps, Microsoft Azure, CI/CD

·        Analytics, Tools and Methods: Tableau, Power BI (DAX), Git, GitHub, JWT Authentication, REST API Design, Agile Delivery