Fully Remote
Employment Type: Full‑Time, Contract
Visa Sponsorship/Processing: Not available
About the Role
We are seeking an AI & Data Semantics Lead to serve as the critical bridge between business stakeholders, data product teams, and AI/LLM engineering groups. This role ensures that enterprise data is clearly defined, consistently governed, and fully understood by AI systems — enabling safer, smarter, and more scalable AI capabilities across the organization.
You will translate complex technical data assets into business‑aligned semantic structures, build and maintain taxonomies and business glossaries, and drive semantic clarity across teams. This is a highly collaborative, business‑facing role that directly impacts AI model performance, agentic workflows, and data product adoption.
Key Responsibilities
LLM & AI Enablement
• Partner with AI/LLM teams to define and govern business meaning for data used in training, inference, and agentic workflows.
• Translate business concepts into structured semantic artifacts (business terms, classifications, relationships).
• Support responsible AI by ensuring data assets have clear definitions, ownership, lineage, and usage constraints.
Business Analysis & Stakeholder Engagement
• Lead discovery sessions with business stakeholders to extract domain knowledge and convert it into reusable semantic assets.
• Act as a trusted translator between business leaders, data product owners, engineers, and AI practitioners.
• Break down ambiguous business questions into clear data concepts and analytical intent.
Metadata, Catalog & Taxonomy Development
• Build and maintain enterprise business glossaries, taxonomies, and classification frameworks within a data catalog environment.
• Enrich technical assets with business context (definitions, relationships, examples, use cases).
• Ensure semantic consistency across domains, data products, and AI use cases.
Data Product & Platform Alignment
• Align semantic definitions with certified data products and governed data sources.
• Partner with data governance, data quality, and lineage teams to ensure metadata completeness and trust.
• Contribute to standards and patterns for AI‑ready metadata and semantic modeling.
Required Qualifications
• 7+ years in business analysis, data analysis, or data product roles.
• Hands‑on experience with data catalog or metadata management platforms (e.g., Alation or similar).
• Proven experience building:
• Business glossaries
• Taxonomies / classification models
• Semantic layers or conceptual data models
• Strong ability to translate technical data assets into clear business language.
• Experience partnering with technical teams (data engineering, analytics, AI/ML).
• Excellent facilitation, documentation, and stakeholder communication skills.
Anna Karoutsos
Talent Sourcing Partner