5 of 5 Permanent Retrieval-Augmented Generation Jobs in Yorkshire

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

to junior consultants Supporting Microsoft partnership activities and training sessions Requirements: Proven experience with Microsoft 365 Copilot, Copilot Studio, and related technologies Strong understanding of AI concepts including LLMs, RAG, and prompt engineering Familiarity with Azure services and cloud ecosystems Excellent communication and presentation skills A passion for mentoring and developing engineering talent Experience with distributed systems and incident response 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 ❯

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 ❯