Senior AI Engineer

The Role

This role will have a significant impact on delivering innovative solutions for one of the leading retailers in the UK, driving digital transformation and enhancing customer experiences. You’ll work on projects that leverage cutting-edge technologies such as microservices, event-driven architectures, and cloud platforms, contributing to scalable, secure, and high-performing systems.

Your responsibilities:

· Design and develop agentic AI systems capable of multi-step reasoning, planning, and action execution

· Build scalable AI applications using Python as the core development language

· Develop and integrate solutions using Azure OpenAI Services, including prompt engineering, embeddings, and fine-tuning strategies

· Implement orchestration pipelines using Semantic Kernel and LangGraph for multi-agent workflows

· Integrate tools, APIs, and enterprise systems using MCP (Model Context Protocol) or similar frameworks

· Design memory, state management, and context-aware agent behaviors

· Optimize performance, cost, and latency of LLM-based solutions

· Collaborate with solution architects, product teams, and stakeholders to translate business use cases into AI solutions

· Ensure governance, security, and responsible AI practices are embedded into solutions

Your Profile

Key Responsibilities

· Design agent architectures

· Define orchestration patterns

· Design tool strategy and integration approach

· Lead implementation of AI services

· Establish coding standards and best practices

· Guide evaluation and safety approaches

· Support production deployments and troubleshooting

Hands-on Skills Required

· Design multi-agent solutions

· Design RAG architecture

· Implement complex orchestration workflows

· Build scalable AI microservices

· Define AI governance patterns

· Troubleshoot production AI solutions

· Productionised AI solution

Must have Technology skills:

· Azure OpenAI

· Azure AI Foundry

· Semantic Kernel

· LangGraph

· MCP

· Azure AI Search

· Event-driven architectures

· Strong proficiency in Python

· Data & Vector Stores: Knowledge of vector databases, embeddings, semantic search and relational/NoSQL databases

· Software Engineering: REST APIs, Docker, Kubernetes, MLOps/LLMOps