Senior Knowledge Engineer Location: Lindau, Germany (preferred) Hybrid: Up to 2 days/week home office (no full-remote) Other Offices: Munich (currently WFH setup) ✈️ Travel: Occasional project visits on-site (rare) About the Role: We are seeking a (Senior) Knowledge Engineer to join our Knowledge Engineering team. In this role, you will design and optimize semantic models, build data pipelines, and work with cutting-edge technologies such as knowledge graphs, semantic data models, and AI-driven solutions (LLMs, RAG, GraphRAG). You will collaborate closely with customers and internal experts to deliver innovative, sustainable solutions. Key Responsibilities: Knowledge & Data Modelling: Design, develop, and maintain knowledge graphs, semantic data models, vector and relational databases. Ontologies & Metadata: Create and refine ontologies, taxonomies, and controlled vocabularies together with subject matter experts. Queries & Data Optimization: Develop SPARQL queries, transform datasets, and continuously optimize semantic models. Consulting & Model Enhancement: Analyze existing knowledge models and adapt them to new requirements. Data Engineering Pipelines: Build and orchestrate data pipelines across company, customer, and cloud infrastructures. AI & Machine Learning: Integrate and optimize LLMs, chatbots, agents, and RAG-/GraphRAG-based systems. Technology Scouting: Evaluate and adopt emerging technologies into customer architectures. Complex Problem Solving: Address challenges with innovative and sustainable solutions. Must-Have Qualifications: At least 3 years of professional experience in Knowledge Engineering, Knowledge Management, or a comparable role. Strong expertise in data/knowledge modelling, semantic technologies, and ontologies. Proficiency in databases, SPARQL, RDF, SHACL. Hands-on programming experience with Python (programming, debugging, deployment). Excellent communication skills in German (C1) and English (C1). Nice-to-Have Qualifications: Certifications in Data Science, Machine Learning, or Project Management. Industry experience in mechanical/plant engineering. Familiarity with tools such as PoolParty, AVM, AnzoGraph DB, Ontotext GraphDB. Experience & Education: Experience: 2–3 years in Knowledge Engineering or similar, with customer project experience and cross-functional collaboration. Education: Degree in Computer Science, Information Science, Knowledge Management, AI, or related field (additional certificates are a plus). Technical Skills: RDF, SPARQL, SHACL, XML, XSLT, DITA, XPath, Java/Python, GraphDB tools.