Associate Director, Semantic & Knowledge Engineering

About the role

Reporting to the Executive Director, Semantic and Knowledge Engineering, the Associate Director designs, builds and governs enterprise semantic models, ontologies, taxonomies, business vocabularies, knowledge graphs, metadata services and semantic APIs. The role supports AI, analytics, enterprise search, interoperability, RAG, agentic AI, contextual search and reasoning engines by embedding reusable semantic capabilities into products and workflows across Strategy, Platforms & Transformation. Two positions are available; the ideal location is East Hanover, with possible remote work subject to legal-entity restrictions, and no relocation provided.

Key responsibilities

• Design, develop and maintain ontologies, taxonomies, business vocabularies and semantic models that give consistent meaning across products, data and AI capabilities.
• Build and enhance knowledge graphs, metadata services and semantic APIs supporting AI, analytics and commercial decision making.
• Work with Product, Applied AI, Analytics Engineering and Platform Engineering teams to embed semantic capabilities into products, workflows and reusable patterns.
• Support semantic foundations for RAG, agentic AI, contextual search, reasoning engines, enterprise search, analytics and interoperability.
• Implement metadata governance, quality controls, stewardship and lifecycle management for enterprise knowledge assets.
• Evaluate emerging semantic technologies and standards, and share reusable engineering patterns and technical guidance.
• Mentor semantic and knowledge engineers and communicate technical trade-offs, risks and recommendations to product, engineering, analytics, AI and business stakeholders.

Required profile

• Bachelor's degree in Computer Science, Information Science, AI, Data Science, Bioinformatics or a related field; advanced degree preferred.
• 6+ years of progressive experience in semantic technologies, knowledge engineering, metadata management, data/information architecture, data product engineering or AI-enabling data platforms.
• Experience building semantic assets for AI grounding, RAG/GraphRAG, enterprise search, reasoning engines, analytics consistency and interoperability.
• Working knowledge of data governance, stewardship, quality controls, access/security, lifecycle management, privacy and compliance.
• Strong engineering delivery discipline, stakeholder management and communication skills.

Required skills

• Ontologies, taxonomies, controlled vocabularies, RDF/OWL, SKOS, SPARQL, graph databases, knowledge graphs, metadata catalogs, data lineage and semantic APIs.
• Desirable: experience in pharmaceutical, healthcare or regulated data environments, and familiarity with FAIR data principles, metadata platforms and cloud-based data and AI ecosystems.

What we offer

• Expected salary range of $176,400 to $327,600 per year, with a performance-based cash incentive and possible annual equity awards.
• Benefits package including health, life and disability coverage, 401(k) with company contribution and match, and a time-off package.