4 of 4 Retrieval-Augmented Generation Jobs in the South West

Data Factory, Azure Synapse, and Azure Functions. Implementing modern retrieval techniques such as vector search, semantic search and Retrieval-Augmented Generation (RAG) using tools like Azure Cognitive Search, FAISS, Pinecone, or Weaviate. Familiarity with data governance, privacy, and ethical AI principles. Experience with DevOps tools and practices, including CI/CD pipelines More ❯

Shop, Sports & Social Club and More Skills Required: Proficiency in Data Science techniques, including statistical models and ML algorithms. Expertise in NLP, with a keen understanding of LLM and RAG technologies. Strong development capabilities, particularly in Python. Experience with data exchange, processing, and storage frameworks (ETL, ESB, API, SQL, NoSQL, and Parquet). Comfort with Agile development methodologies. Excellent teamwork More ❯

Experience working with LLMs and prompt design (ideally OpenAI or similar) An understanding of structured data (SQL, JSON, CSV) and unstructured text (PDFs Exposure to RAG architectures and vector stores (such as FAISS, Pinecone...) Prompt Engineer (AI & Data) – Could suit a Graduate/Junior or Experienced professional Location: Remote (M4/M5/M50 area preferred but flexible) Salary … the join the R&D team and design, test and refine prompts , clean and map unstructured text and structured fields into usable metadata and semantic indexes for use in RAG systems and collaborate with product and design teams to embed LLM-powered assistants into customer facing healthcare support tools. What You'll Do Work across LLM design, structured data integration … Bring Experience working with LLMs and prompt design (ideally OpenAI or similar) An understanding of structured data (SQL, JSON, CSV) and unstructured text (PDFs, documents, form data) Exposure to RAG architectures and vector stores (such as FAISS, Pinecone.....) The ability to work with and communicate with multi-disciplinary teams at all levels of an organization Any experience in a professional More ❯

support secure, air-gapped AI deployments, with a focus on NLP-based tooling * Develop pipelines for transcription ingestion and real-time analytical insight generation * Support graph and RAG-based inference layers using data from structured and unstructured sources * Build and expose APIs for frontend consumption, enabling natural-language querying, dynamic visualisation, and reporting * Ensure system portability via containerisation … clear grasp of the constraints and workarounds involved * Comfort designing APIs for real-time and batch AI/ML pipelines. * Experience supporting or building graph-based systems (e.g., for RAG or knowledge graph traversal) is a plus Experience working with LLMs, vector stores, or transcription pipelines Experience in Defence, aerospace, or other secure environments Due to the nature and urgency More ❯