You'll shape how AI is applied to create, structure, classify, govern, and continuously improve enterprise knowledge, with a primary focus on unstructured content and knowledge assets.
It strengthens access to trusted knowledge across the organisation by: advancing content governance and lifecycle processes for the corporate intranet and quality-assured document and contract management systems; enabling content communities through clear ownership, standards, and practical guidance; and by establishing AI-readiness standards for content structures, taxonomies, metadata, ontologies, and content management practices.
The role does so in close collaboration with IT architects, IT service owners, Data & AI Science, and business communities.
All the responsibilities we'll trust you with:
You'll own and continuously improve AI-assisted ex ante and ex post quality-assurance processes across the lifecycle of unstructured content and knowledge assets, from creation to retirement. Combine preventive standards and monitoring to improve accuracy, consistency, completeness, and trustworthiness.
You'll also define and maintain measurable AI-readiness criteria and certification for unstructured content and knowledge assets, covering structure, metadata, ownership, currency, accessibility, and semantic clarity. Apply them across priority repositories and content types to qualify trusted sources for search, retrieval, and agentic AI.
You'll own machine-readable templates and AI assisted authoring standards for priority content types, including policies, procedures, guidelines, knowledge articles, and contracts. Convert business, governance, metadata, and structural requirements into reusable templates that improve authoring consistency and enable automated validation, classification, retrieval, and AI reuse.
Furthermore, you'll establish and drive adoption of standards and guardrails for AI-assisted content creation, including approved use cases, authoring guidance, prompt patterns, human review, source traceability, and quality controls. Work with content communities, domain experts, content owners, Data & AI Science, and IT to embed them in workflows without compromising accuracy, compliance, ownership, or editorial accountability.
You’ll own persona-based reporting across priority repositories and domains for framework owners, content managers, content owners, and content editors. Define indicators for quality, ownership, lifecycle, usage, compliance, and AI-readiness, and provide actionable dashboards for prioritisation, governance decisions, and accountability.
You'll also monitor unstructured content and knowledge assets against agreed standards, identify systemic gaps and root causes, and coordinate corrective action with content owners, business communities, domain experts, Data & AI Science, and IT. Track remediation and use insights to improve governance, quality checks, templates, training, and platform capabilities.
You'll operate a federated governance model for unstructured content and knowledge assets across priority repositories and domains. Define decision rights, ownership, accountability, escalation paths, lifecycle controls, and minimum quality requirements, embedding them consistently in repository processes and platforms.
You'll build and coordinate business content communities of framework owners, content managers, content owners, and content editors. Provide guidance, training, reusable standards, and collaboration forums, working with domain experts, Data & AI Science, and IT to drive adoption, share practices, and resolve cross-functional governance issues.
You'll operate operate taxonomy and ontology management for unstructured content and knowledge assets across priority repositories and domains. Define modelling standards, semantic ownership, approval, versioning, and maintenance so controlled vocabularies, concepts, relationships, classifications, and metadata remain consistent, interoperable, and aligned with business terminology.
You'll partner with domain experts, content owners, Data & AI Science, and IT to develop and extend machine-readable semantic models using RDF, OWL, SKOS, and SHACL. Translate business concepts and relationships into governed structures supporting metadata enrichment, classification, knowledge graphs, semantic search, retrieval-augmented generation, and reliable agentic AI.
You'll champion continuous innovation by monitoring emerging practices, technologies, and market developments in content governance, knowledge management, and agentic AI. Regularly assess the effectiveness of implemented solutions, identify opportunities for optimisation, and translate relevant advances into scalable improvements that keep platforms, processes, and standards effective, user-focused, and aligned with state-of-the-art capabilities.
that matter most for this role:
In the 1980s Dietrich Mateschitz developed a formula known as the Red Bull Energy Drink. This was not only the launch of a completely new product, in fact it was the birth of a totally new product category.
The company beyond the canChasing our potential
Since the early days of Red Bull, an entrepreneurial mindset has always guided our approach to work and the environment we create:
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