Stott and May
Senior AI Engineer
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Senior AI Engineer
Location: London, UK (Hybrid – 1 Day Per Week Onsite)
Day Rate: £600 per day (Inside IR35)
Contract Duration: 6 Months
Overview
We are supporting a leading UK organisation in their search for a Senior AI Engineer to join a major digital transformation programme. This role will focus on designing and delivering next-generation AI solutions using Large Language Models (LLMs), agentic AI frameworks, and cloud-native technologies. Working closely with architects, engineering teams, and business stakeholders, you will develop scalable, secure, and production-ready AI applications that solve complex business challenges while driving innovation across the organisation.
Key Responsibilities
- Design and develop agentic AI systems capable of multi-step reasoning, planning, and execution.
- Build scalable AI applications using Python.
- Develop and integrate solutions using Azure OpenAI Services.
- Design orchestration pipelines using Semantic Kernel and LangGraph.
- Integrate enterprise systems, APIs, and tools using MCP or similar frameworks.
- Design memory management, context handling, and intelligent agent behaviours.
- Optimise AI solutions for performance, scalability, latency, and cost.
- Lead the implementation of AI services and establish engineering best practices.
- Design Retrieval-Augmented Generation (RAG) architectures.
- Define AI orchestration patterns and multi-agent workflows.
- Embed governance, security, and responsible AI principles into solutions.
- Support production deployments, monitoring, and troubleshooting.
- Collaborate with technical and business stakeholders to translate requirements into AI solutions.
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Essential Skills & Experience
- Proven experience designing and building enterprise AI solutions.
- Strong Python development skills.
- Hands-on experience with Azure OpenAI Services.
- Experience designing multi-agent AI architectures.
- Strong understanding of Retrieval-Augmented Generation (RAG) architectures.
- Experience with Semantic Kernel and LangGraph.
- Knowledge of Model Context Protocol (MCP) or similar integration frameworks.
- Experience building scalable AI microservices.
- Strong understanding of event-driven architectures.
- Experience integrating AI solutions with enterprise APIs and systems.
- Knowledge of AI governance, security, and responsible AI principles.
- Experience deploying and supporting AI solutions in production.
- Strong stakeholder engagement and communication skills.
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Desirable Skills
- Experience with Azure AI Foundry.
- Experience with Azure AI Search.
- Knowledge of prompt engineering, embeddings, and model fine-tuning.
- Experience designing cloud-native AI platforms on Microsoft Azure.
- Familiarity with microservices architectures.
- Experience working on enterprise-scale digital transformation programmes.
- Exposure to MLOps, AI observability, and model monitoring.
- Experience mentoring engineers or providing technical leadership.
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