Expire in: a month
Location: Hybrid (London preferred)
Contract: 6–12 months (Outside IR35)
Rate: £500–£700/day (DOE)
Looking for an experienced AI Engineer to design and implement Graph-based Retrieval-Augmented Generation (GraphRAG) pipelines for enterprise-scale AI solutions. This is a hands-on role working on cutting-edge projects in knowledge graph construction, multi-hop reasoning, and hybrid retrieval systems.
Key Responsibilities
Build and optimize GraphRAG pipelines integrating LLMs with knowledge graphs.
Develop graph-based retrieval strategies and combine them with vector search for hybrid RAG.
Implement graph traversal algorithms and entity-relation extraction from unstructured data.
Collaborate with data scientists and engineers to deploy scalable AI solutions.Required Skills
Strong experience with GraphRAG or Graph-based RAG architectures.
Proficiency in Python and frameworks like LangChain, Semantic Kernel, or similar.
Hands-on with graph databases (Neo4j, TigerGraph) and vector DBs (Pinecone, Weaviate, FAISS).
Knowledge of LLMs, prompt engineering, and retrieval optimization.
Familiarity with knowledge graph construction, entity linking, and graph algorithms.Must have full right to work and live in the UK to be considered for this roleDo not include the following in your job application, CV, or cover letter:
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