Senior Specialist – Knowledge Semantics and AI-Ready Content

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.
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.

Employment type
Full-time

Work arrangement
No