AI & Data Semantics Lead (Business-Facing) - Remote - Banking - Direct Client - JOBID687

We are seeking an AI & Data Semantics Lead to accelerate our LLM and AI model teams by serving as the critical bridge between business stakeholders, data products, and technical AI teams. This role is responsible for translating complex technical data assets into clear, governed, business-understandable semantics that can be safely and effectively leveraged by AI models. The ideal candidate is exceptionally strong in business analysis, comfortable working in enterprise data catalog environments.Key ResponsibilitiesLLM & AI EnablementPartner with LLM and AI model teams to define, document, and govern business meaning for data assets used in training, inference, and agentic workflows.Translate business concepts into structured semantic artifacts (business terms, classifications, relationships) consumable by AI systems.Support responsible AI by ensuring data assets have clear definitions, ownership, lineage context, and usage constraints.Business Analysis & Stakeholder EngagementLead 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.Decompose ambiguous business questions into well-defined data concepts and analytical intent.Metadata, Catalog & Taxonomy DevelopmentBuild and maintain enterprise business glossaries, taxonomies, and classification frameworks within a data catalog environment.Curate and enrich technical assets with business context (descriptions, relationships, use cases, examples).Ensure semantic consistency across domains, data products, and AI use cases.Data Product & Platform AlignmentAlign semantic definitions with data products, certified assets, 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 Qualifications7+ years of experience in business analysis, data analysis, or data product rolesDemonstrated experience working in a data catalog or metadata management platform (e.g., Alation or equivalent)Hands-on experience building:Business glossariesTaxonomies / classification modelsSemantic layers or conceptual data modelsStrong ability to translate technical data assets into business languageProven experience partnering with technical teams (data engineering, analytics, AI/ML)Excellent facilitation, documentation, and stakeholder communication skills