Associate Director, Semantic & Engineering

Position: Associate Director, Semantic & Knowledge Engineering (2 Openings)
Job Description Summary #LI-Hybrid Reporting to the Executive Director, Semantic and Knowledge Engineering, the Associate Director, Semantic and Knowledge Engineering designs, builds, and governs enterprise semantic models, ontologies, taxonomies, business vocabularies, knowledge graphs, metadata services, and semantic APIs. The role enables AI, analytics, enterprise search, interoperability, retrieval-augmented generation (RAG), agentic AI, contextual search, and reasoning engines by embedding reusable semantic capabilities into products and workflows across Strategy, Platforms & Transformation.

The ideal location for this role is East Hanover but remote work may be possible (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. If associate is remote, all home office expenses and any travel/lodging to specific East Hanover for periodic live meetings will be at the employee’s expense.

The expectation of working hours and travel (domestic and/or international) will be defined by the hiring manager. This position will require 10% travel.

There are 2 positions available.

Job Description

Key Responsibilities:

Enterprise semantic modeling and knowledge engineering
• Design, develop, and maintain enterprise ontologies, taxonomies, business vocabularies, and semantic models that establish consistent meaning across products, data, and AI capabilities.
• Build and enhance knowledge graphs, metadata services, and semantic APIs that support AI, analytics, enterprise applications, and commercial decision enablement. Semantic capabilities for AI and product workflows
• Collaborate with Product, Applied AI, Analytics Engineering, and Platform Engineering teams to embed semantic capabilities into products, workflows, platforms, and reusable solution patterns.
• Support semantic foundations for RAG, agentic AI, contextual search, reasoning engines, enterprise search, analytics, and interoperability initiatives. Metadata governance and knowledge lifecycle management
• Implement metadata governance, semantic quality controls, stewardship practices, and lifecycle management for enterprise knowledge assets.
• Promote quality, consistency, reuse, transparency, and governed evolution of semantic assets across the SPT ecosystem. Technology evaluation and architecture evolution
• Evaluate emerging semantic technologies, standards, graph capabilities, and knowledge engineering approaches to inform the evolution of the enterprise knowledge architecture.
• Contribute reusable engineering patterns and technical guidance that reduce duplication and improve scalability across semantic and knowledge engineering work. Technical mentorship and cross-functional collaboration
• Mentor semantic and knowledge engineers while promoting reusable engineering patterns, technical excellence, disciplined documentation, and pragmatic implementation.
• Communicate technical trade-offs, risks, dependencies, and recommendations clearly to product, engineering, analytics, AI, and business stakeholders. Essential Requirements:

Education:

Bachelor's degree in Computer Science, Information Science, Artificial Intelligence, Data Science, Bioinformatics, or a related discipline; 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. Hands-on experience designing and maintaining ontologies, taxonomies, controlled vocabularies, business glossaries, semantic models, RDF/OWL, SKOS, SPARQL, graph databases, knowledge graphs, metadata catalogs, data lineage, and semantic APIs/services.

Experience building…