About this role
Knowledge & Semantics Engineer d/f/m Location(s): Essen, NW, DE, 45141 RWE AG To start as soon as possible, full time / part time, permanent As a hands-on Knowledge & Semantics Engineer you build and operate the layer that gives our AI and agents context. You will engineer the knowledge graphs, semantics and retrieval that agents reason over, turning domain know-how into reliable, governed context. About the role - Build and operate knowledge graphs and the semantic layer across domains, federated but interoperable, from modelling through to running pipelines. - Implement master data management and business-rule logic, and maintain the ontology and shared semantics that connect domains. - Engineer and optimise RAG and retrieval solutions, including chunking, embeddings, indexing, grounding, and evaluation, to deliver accurate, explainable, and reliable AI outcomes. - Expose knowledge to agents as reliable, governed context and callable tools, including via MCP. - Automate knowledge-curation pipelines and quality checks, and catalogue knowledge assets to avoid fragmented, unmanaged stores. - Work with business experts to capture domain know-how and turn it into reusable knowledge products. Job requirements and experience - University degree (or equivalent) in Computer Science, Computer Engineering, Information Technology or related field. - Hands-on working experience in handling data modelling and understanding of Data ecosystems. - Skills in building knowledge graphs and semantic models, with graph / semantic tooling (e.g. Stardog, Neo4j or similar) and query languages (SPARQL, Cypher or GraphQL). - Skills in RAG engineering for LLMs and agents: embeddings, vector stores, retrieval pipelines, grounding and evaluation. - Know How of Master data management and ontology / taxonomy modelling (e.g. SAP MDG or equivalent). - Strong data engineering foundations: Python, SQL, pipelines and CI/CD. - The ability to translate business ...