Senior Python AI Engineer

Overview

In this role you design and ship production AI-powered services for an enterprise HR platform. You will implement agentic workflows, RAG pipelines, and scalable APIs using Python across a modern AI stack, striving for reliability and scale. You’ll collaborate with architects and product teams to turn requirements into robust technical solutions and shape how AI is used in enterprise software. This is a hands-on, impact-focused role at the cutting edge of generative AI, with opportunities to influence architecture and tooling. You’ll work in a cross-functional team that values craft and practical value from AI.

Pay / Benefits

• 25 days annual leave
• private healthcare
• group income protection
• pension scheme with matched contributions up to 10%
• hybrid working
• volunteer day

Responsibilities

• Design, develop and maintain AI-powered application services using Python
• Build and evolve agentic workflows and AI orchestration with LangGraph and LangChain
• Develop scalable APIs and backend services with FastAPI
• Design RAG pipelines integrating LLMs with enterprise data sources
• Implement retrieval strategies (vector, metadata, graph-based)
• Contribute to complex AI workflows with multiple agents, tools and data
• Integrate AI services with HR Expert app and enterprise systems
• Develop and deploy solutions on Microsoft Azure across varied data stores
• Collaborate across teams to translate requirements into solutions
• Promote testing, observability, performance and maintainability of AI apps
• Explore emerging AI technologies for practical value
• Occasionally contribute to frontend or .NET services when needed

Key requirements

• Strong Python development experience in production apps
• Experience building APIs/backends, ideally FastAPI
• Proven experience with LLMs using LangChain/LangGraph and agentic workflows
• Experience developing RAG solutions and integrating multiple data sources via REST APIs
• Solid engineering practices: automated testing, source control, code reviews, CI/CD
• Understanding of production generative AI challenges: retrieval, grounding, context management, evaluation, reliability, performance

• clear communication with technical and non-technical stakeholders
• ownership of quality and reliability
• problem solving and learning mindset
• LangGraph
• LangChain
• FastAPI

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