5 of 5 Retrieval-Augmented Generation Jobs in Newcastle upon Tyne

Model programme for a central government department. Where the Lead Technical Architect sets direction, you turn it into working, production-grade systems - semantic search, RAG pipelines, and broader generative AI capability - integrated into complex Legacy and multi-cloud environments handling high-volume, sensitive public sector data. You'll work inside … eventually run these systems without long-term reliance on external suppliers. Key ResponsibilitiesHands-On Build & Delivery Design, build, and ship production AI components - RAG pipelines, retrieval and embedding infrastructure, orchestration logic, and integration layers - writing high-quality, tested, maintainable code and staying close to implementation rather than delegating ...

Model programme for a central government department. Where the Lead Technical Architect sets direction, you turn it into working, production-grade systems - semantic search, RAG pipelines, and broader generative AI capability - integrated into complex Legacy and multi-cloud environments handling high-volume, sensitive public sector data. You'll work inside … eventually run these systems without long-term reliance on external suppliers. Key Responsibilities Hands-On Build & Delivery Design, build, and ship production AI components - RAG pipelines, retrieval and embedding infrastructure, orchestration logic, and integration layers - writing high-quality, tested, maintainable code and staying close to implementation rather than ...

client is a global professional services and technology consultancy. We are building the next generation of AI-native engineering talent engineers who use AI as a core part of how they work, not as an add-on. As an AI Engineer (Software), you will design, build, and ship … improve AI-generated outputs; understanding of AI limitations and responsible use Familiarity with agentic system concepts awareness of orchestration frameworks (LangChain, LangGraph, or equivalent), RAG pipelines, and how full-stack applications connect to agent-based architecture; production experience preferred, conceptual understanding required About our client Our client is a leading ...

direct pathway to the Forward Deployed Engineer programme. Key Responsibilities Design and build production-grade agentic solutions end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning … depth, not tutorial level Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering LLMOps fundamentals: eval harness design, prompt versioning, and production observability Cloud-native engineering maturity: Kubernetes ...

across Artificial Intelligence and Machine Learning. We are open to candidates with different areas of expertise, including Machine Learning, Applied AI, Generative AI, LLMs, RAG and Agentic AI. Key Responsibilities Design and develop AI/ML solutions from early-stage concepts through to production. Develop, evaluate and integrate AI/… models and applications. Work across modern AI technologies including LLMs, RAG, NLP, Computer Vision and agent-based systems. Assess model performance, investigate failure modes and optimise solutions. Develop robust, high-quality Python software for technically complex applications. Work closely with experienced engineers, technical specialists and customers to solve challenging real ...