Knowledge Graph & GenAI Lead

Job DescriptionKnowledge Graph & GenAI LeadLondon | RemoteUp to 900 per day or Perm roles available +/- for the best candidate.Global AI & analytics firm operating at the intersection of knowledge graphs, generative AI, and enterprise transformation.This role requires you to embed graph intelligence into mission-critical systems enabling explainable AI, unified data views, and advanced reasoning across regulated industries and industrial domains.You will drive the design, build, and deployment of knowledge graph + GenAI systems for high-impact clients. Youll be part of a small elite team, bridging data, AI, and business outcomes from model scoping through to production launch.Ship full systemsOperate in regulated or industrial domains (e.g. manufacturing, life sciences, public sector)Embed client strategy and technical teamsStretching the frontier: hybrid KG + AI, graph + reasoning + M ResponsibilitiesLead KG schema & ontology design across domains (assets, risk, supply chain, compliance)Build ingestion pipelines (ETL / streaming / CDC) and entity resolution for graph populationAuthor complex queries (Cypher, GSQL, AQL, SPARQL etc. depending on stack)Integrate knowledge graph retrieval & reasoning into LLM / RAG / GraphRAG systemsDevelop and evaluate graph ML / embedding models (link prediction, anomaly detection)Optimize graph performance, scaling, and query efficiencyLiaise with client stakeholders: translate business problems into graph solutionsMentor junior engineers, contribute to propositions, and support POCs Must-Have Skills & Experience5+ years in engineering, data, or AI rolesDeep experience with at least one graph technology: Neo4j, TigerGraph, ArangoDB, OrientDB, or StardogProficiency in query languages (Cypher, GSQL, AQL, SPARQL, etc.)Strong background in pipelines, ETL, and entity resolutionExposure to integrating KG + LLM or RAG architecturesExperience with graph algorithms, embeddings, or GNNsCloud & production engineering literacy (AWS/Azure/GCP, containerization, CI/CD)Excellent communication skills able to explain complex graph/AI concepts to non-technical audiences Nice-to-Have / Bonus AssetsExperience with GraphRAG or KG-backed LLM retrievalSemantic web / ontology skills (RDF/OWL/SHACL)Prior consulting or client delivery backgroundGraph visualization / UI experience (Linkurious, Bloom, Ogma)Graph DB certifications (Neo4j, Stardog, etc.)High visibility & critical client impactExposure to cutting-edge hybrid AI / KG architecturesAutonomy, ownership, and fast learningCompetitive compensation + meaningful equity or bonus schemeFlexible / hybrid work arrangement

Created: 2025-11-05