Senior Knowledge Engineer
If you are passionate about semantic technologies, AI, and knowledge management and want to work in a collaborative, innovative environment, we’d love to hear from you!
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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.
- Department
- Information Technology
- Locations
- Germany
- Employment type
- Full-time
- Employment level
- First /Mid-Level Officials
- Job location
- Lindau, Germany
- Employment Level | Seniority
- Mid-Senior level
Sperton
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