1 of 1 Permanent Retrieval-Augmented Generation Jobs in North Yorkshire

that represent Comply’s financial and regulatory data in vector space. Build and operate vector database infrastructure for semantic search and similarity retrieval. Implement RAG architectures that ground LLM outputs in Comply’s proprietary data, and evaluate and integrate LLM tooling suited to our use cases. Build reliable, observable data … Jena Fuseki, Neo4j, Amazon Neptune, or equivalent). Experience with vector databases and embedding pipelines (e.g., Pinecone, Weaviate, Qdrant, pgvector). Practical experience implementing RAG architectures or LLM-integrated data pipelines. Familiarity with semantic web standards—JSON-LD, RDF, OWL, or SKOS. Strong Python skills and experience with data pipeline ...