Job
- Level
- Erfahren
- Job Feld
- Software, Data
- Anstellung
- Teilzeit / Vollzeit
- Vertragsart
- Unbefristetes Dienstverhältnis
- Ort
- Essen
- Arbeitsmodell
- Hybrid, Onsite
Job Zusammenfassung
In diesem Job entwickelst du Wissen und semantische Modelle, baust und pflegst Wissensgraphen sowie Retrieval-Pipelines, um kontextbasierte und erklärbare KI-Lösungen für Agenten zu liefern.
Job Technologien
Deine Rolle im Team
- 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.
- 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.
Unsere Erwartungen an dich
Ausbildung
- University degree (or equivalent) in Computer Science, Computer Engineering, Information Technology or related field.
Qualifikationen
- 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 meaning into working technical implementation, and to elicit know-how from domain experts.
- Familiarity with MCP and modern agent frameworks.
Erfahrung
- Hands-on working experience in handling data modelling and understanding of Data ecosystems.
- Experience grounding agents or LLM applications in enterprise knowledge at scale.
Unser Angebot
- Independent work on exciting and responsible tasks.
- Close collaboration in a motivated team with an open feedback culture that promotes your personal and professional development.
- Insights into a global energy company.
- Hybrid working and flexible working time models.
- Free access to the Health Center, modern open workspaces, free parking, e-charging stations and much more.
- Structured and digitized pre- and onboarding process supported by the web-based app RWE+You.
Benefits
Work-Life-Integration
Mehr Netto
Gesundheit, Fitness & Fun
Essen & Trinken
Themen mit denen du dich im Job beschäftigst
Job Standorte
Das ist dein Arbeitgeber
RWE AG
Die RWE AG ist ein unverzichtbarer Bestandteil des europäischen Energiesystems und sorgt für die Versorgungssicherheit in Europa. Das Unternehmen verfügt über drei operative Segmente: Braunkohle & Kernenergie, Europäische Stromerzeugung aus Gas, Kohle, Wasserkraft und Biomasse sowie Energiehandel. Zudem hält RWE eine Finanzbeteiligung an der innogy SE, einem der führenden europäischen Energieunternehmen.
Description
- Unternehmensgröße
- 250+ Employees
- Unternehmenstyp
- Etablierte Firma
- Arbeitsmodell
- Hybrid, Onsite
- Branche
- Energiewirtschaft, Umwelt
Knowledge & Semantics Engineer
- Ort
- Essen
- Arbeitsmodell
- Hybrid, Onsite
- Diversität
- Für alle Personen geeignet (m/w/d)
- Nur Englisch
- Nur Englisch erforderlich
