Below is a rewritten version of the job description reflecting that it is a contract role, does not include a client name or rate, and clearly states that visa sponsorship is not available.
Contract Position
Visa sponsorship is not available for this role.
We are seeking an experienced AI & Data Semantics Lead to accelerate LLM and AI model initiatives by serving as the strategic bridge between business stakeholders, data product teams, and technical AI practitioners.
This role focuses on translating complex technical data assets into clear, governed, business-friendly semantic structures that AI systems can reliably interpret and leverage. You will play a critical role in ensuring AI models understand not just where data resides, but what it means.
The ideal candidate brings strong business analysis expertise, hands-on experience within enterprise data catalog environments, and a proven track record building scalable taxonomies, business glossaries, and semantic layers that support cross-functional AI and data initiatives.
Partner with AI and LLM teams to define, document, and govern the business meaning of data assets used in training, inference, and agentic workflows.
Translate business concepts into structured semantic artifacts (business terms, classifications, relationships) consumable by AI systems.
Promote responsible AI practices by ensuring data assets have clear definitions, ownership, lineage context, and usage constraints.
Lead discovery sessions with business stakeholders to capture domain knowledge and convert it into reusable semantic assets.
Act as a trusted intermediary between business leaders, data product owners, engineers, and AI/ML teams.
Break down ambiguous business problems into clearly defined data concepts and analytical intent.
Design, build, and maintain enterprise business glossaries, taxonomies, and classification frameworks within a data catalog or metadata management platform.
Curate and enrich technical data assets with business context, including descriptions, relationships, use cases, and examples.
Ensure semantic alignment and consistency across domains, data products, and AI use cases.
Align semantic definitions with governed data sources, certified data assets, and data products.
Collaborate with data governance, data quality, and lineage teams to strengthen metadata completeness and trust.
Contribute to best practices and standards for AI-ready metadata and semantic modeling.
7+ years of experience in business analysis, data analysis, data governance, or data product roles.
Hands-on experience working within a data catalog or metadata management platform (e.g., Alation or similar).
Demonstrated experience building:
Business glossaries
Taxonomies and classification models
Semantic layers or conceptual data models
Strong ability to translate complex technical data assets into clear business language.
Proven experience collaborating with technical teams, including data engineering, analytics, and AI/ML.
Excellent facilitation, documentation, and stakeholder communication skills.