Company Description
Great AI starts with great knowledge.
You'll be at the forefront of making enterprise knowledge ready for the next generation of AI. With your expertise in semantics and content quality, you'll turn unstructured information into trusted, accessible, and machine-readable knowledge that powers intelligent search and agentic AI.
As part of our Global Data Knowledge Management team, you'll drive AI-readiness standards, shape smarter content governance, and collaborate across business and technology teams to unlock the full potential of our enterprise knowledge.
Job Description
CONTENT QUALITY FRAMEWORKS AND PROCESS
You'll develop and run AI-assisted quality assurance processes across the lifecycle of unstructured data and knowledge assets, combining preventive standards and monitoring to strengthen accuracy, consistency, completeness, and trustworthiness.
You'll develop and maintain measurable AI-readiness criteria and certification for structure, metadata, ownership, currency, accessibility, and semantic clarity, qualifying priority repositories and content types as trusted sources for people, retrieval, and agentic AI.
You'll facilitate federated governance for unstructured data and knowledge assets across priority repositories and domains.
INSIGHTS, MONITORING AND CONTINUOUS IMPROVEMENTS
You'll build persona-based reports and dashboards that expose gaps and drive root-cause fixes.
You'll monitor knowledge assets, track remediation, and use insights to improve governance, quality checks, templates, training, and platforms.
TAXONOMY, ONTOLOGY AND SEMANTIC MANAGEMENT
As a semantics expert, you'll operate taxonomy and ontology management across priority repositories and domains, defining modelling standards and governance to ensure consistency, interoperability, and alignment with business terminology.
You'll translate business concepts into governed structures supporting metadata enrichment, classification, knowledge graphs, semantic search, retrieval-augmented generation, and reliable agentic AI.
AI-ASSISTED CONTENT AUTHORING
You'll develop machine-readable templates and AI-assisted authoring standards for priority content types, including policies, procedures, guidelines, knowledge articles, and contracts.
You'll facilitate standards and guardrails for AI-assisted authoring, including approved use cases, guidance, prompt patterns, human review, source traceability, and quality controls.
Qualifications
Degree in information science, knowledge management, linguistics, cognitive science, data science, computer science, or a related field.
Experience applying semantic technologies and governed knowledge to generative AI, RAG, or agentic AI use cases.
Analytical mindset to assess content performance, identify gaps, and drive improvements.
Ability to translate business needs into ontologies and clear content structures.
Strong practical knowledge of RDF, OWL, SKOS, and SHACL and ontology management.
Python and SPARQL; SQL is an advantage.
Power BI experience.
Experience with AI-enabled content workflows, semantic search, automated classification, metadata enrichment, or AI features for knowledge platforms is an advantage.
Additional Information
Due to legal reasons, we are obliged to disclose the minimum salary according to the collective agreement for this position, which is € 2,509 gross per month. However, our attractive compensation package is based on market-oriented salaries and is therefore significantly above the stated minimum salary.
As an employer, we value diversity and support people in developing their potential and strengths, realizing their ideas and seizing opportunities. We believe passionately that employing a diverse workforce is central to our success. We welcome applications from all members of society irrespective of age, skin colour, religion, gender, sexual orientation or origin.
Summary
Develop and operate AI-readiness, quality, and governance frameworks for enterprise unstructured knowledge, including certification, monitoring, and remediation. Model taxonomies and ontologies using RDF, OWL, SKOS, SHACL, Python and SPARQL to power semantic search, RAG, and agentic AI. Requires degree in related field and applied semantics experience.
Responsibilities
Develop and run AI-assisted quality assurance processes for unstructured data; maintain AI-readiness criteria and certification for trusted sources; facilitate federated governance; build reports and dashboards; operate taxonomy and ontology management; develop machine-readable templates and AI-assisted authoring standards
Qualifications
Degree in information science, knowledge management, linguistics, cognitive science, data science, computer science, or related field; experience applying semantic technologies to generative AI, RAG, or agentic AI; strong practical knowledge of RDF, OWL, SKOS, SHACL and ontology management; Python and SPARQL; SQL is an advantage; Power BI experience
Education requirements
Degree in information science, knowledge management, linguistics, cognitive science, data science, computer science, or a related field
Experience requirements
Experience applying semantic technologies and governed knowledge to generative AI, RAG, or agentic AI use cases; analytical mindset to assess content performance