3 of 3 Contract Retrieval-Augmented Generation Jobs in the North of England

architect/engineer who understands how to construct and integrate hybrid agenticworkflows and toolchains including local agents, SLM/Vector DB's, MCP/RAG/fine-tuning models. 1.Solid engineering experience with CoPilot/Agentic tools (Github CoPilot preferred), across moden cloud native engineering (GCP preferred), with solid grounding ...

Foundry environment. This is a hands-on role focused on building scalable, production-ready AI systems using LLMs, RAG (retrieval augmented generation), vector databases, embeddings and Azure AI services. Key Responsibilities Design and develop LLM-powered applications, AI agents and Copilot solutions Build … optimise RAG pipelines, embeddings and vector search Integrate AI solutions with enterprise systems, APIs and cloud platforms (Azure) Implement secure-by-design AI engineering, monitoring and observability Develop reusable components including prompt libraries, agent frameworks and connectors Prototype, test and improve model performance, reliability and scalability Key Skills Strong experience ...

enterprise-grade AI capabilities. What Youll Be Doing Designing and building Copilot solutions, intelligent agents, and LLM workflows Developing scalable AI components including RAG pipelines, embeddings, and vector search Integrating AI solutions into enterprise systems, APIs, and cloud platforms Conducting rapid prototyping to validate use cases, UX, and model performance … Essential Skills for the AI product developer Proven experience building solutions using LLMs, AI APIs, and Copilot Studio or similar tools Strong understanding of RAG architectures, vector databases, and embeddings Experience with Azure AI and cloud-native development Solid knowledge of secure engineering practices including authentication, data protection, and auditability ...