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
