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Red Bull Data Service GmbH is seeking a Senior Specialist to lead knowledge semantics and AI-ready content. You will shape governance, taxonomy, and semantic standards to prepare unstructured data for AI, including content templates and metadata enrichment.
You will design ontologies and governance across domains, implement RDF/OWL/SKOS/SHACL practices, and collaborate with IT and business teams to empower intelligent search and agentic AI.
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.
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.
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.
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.
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.
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.
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.
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