2 of 2 Retrieval-Augmented Generation Jobs in Wetherby

its business milestones. Responsibilities (including but not limited to): Backend APIs (Python/FastAPI): Build reliable, secure services that power AI features and data retrieval at scale. RAG & vector search: Design, implement and iterate retrieval pipelines (chunking, embeddings, hybrid search, ranking, feedback loops). Own pgvector/Vector DB schemas, latency, relevance and cost. LLM integration … hardworking and dedicated, with an entrepreneurial/ownership mindset, strong communication skills and a team player 5+ years of professional experience in full-stack development. Hands-on experience with RAG systems , vector databases (pgvector/FAISS/Weaviate/ES k-NN), embeddings , and hybrid search (BM25 + vectors). Strong grasp of chunking strategies , metadata, indexing, recall/precision More ❯

its business milestones. Responsibilities (including but not limited to): Backend APIs (Python/FastAPI): Build reliable, secure services that power AI features and data retrieval at scale. RAG & vector search: Design, implement and iterate retrieval pipelines (chunking, embeddings, hybrid search, ranking, feedback loops). Own pgvector/Vector DB schemas, latency, relevance and cost. LLM integration … hardworking and dedicated, with an entrepreneurial/ownership mindset, strong communication skills and a team player 5+ years of professional experience in full-stack development. Hands-on experience with RAG systems, vector databases (pgvector/FAISS/Weaviate/ES k-NN), embeddings, and hybrid search (BM25 + vectors). Strong grasp of chunking strategies, metadata, indexing, recall/precision More ❯