Novartis
Executive Director, Semantic and Knowledge Engineering
$225K–$419K
East Hanover +1 · Director · Full-time · Posted Aug 23, 2026
- Location
- East Hanover
Distant Employee - Distant Working Arrangement (DWA) (USA) - Experience
- 10+ years in semantic technologies, knowledge engineering, enterprise architecture, data management, or AI platforms, including leadership experience.
- Education
- Bachelor's or advanced degree in Computer Science, Information Science, Artificial Intelligence, Data Science, Bioinformatics, or a related discipline.
About the job
Leads the strategy, architecture, and delivery of Novartis’s enterprise semantic layer and knowledge engineering capabilities for NovaOS and AI-enabled enterprise intelligence.
What you'll do
- Define and execute enterprise strategy for semantic technologies, knowledge engineering, and knowledge graphs; lead ontology, taxonomy, vocabulary, and semantic model development and governance.
- Design and implement a semantic layer, and establish governance, metadata management, lifecycle processes, and quality standards for knowledge assets.
- Partner across teams to embed semantic capabilities in products and AI solutions; lead a team of semantic, ontology, and knowledge engineers.
What they ask for
- Bachelor's or advanced degree in Computer Science, Information Science, Artificial Intelligence, Data Science, Bioinformatics, or a related discipline.
- Deep expertise with ontologies, taxonomies, metadata, RDF/OWL, knowledge graphs, graph databases, semantic web technologies, and enterprise information architecture.
- Experience building enterprise semantic platforms for AI, analytics, search, and data interoperability at scale.
- Leadership, executive communication, and cross-functional stakeholder management skills.
Nice to have
- Experience applying semantic technologies to generative AI, agentic AI, RAG, and enterprise AI platforms.
- Experience in pharmaceutical, healthcare, or other highly regulated industries.
Pay
$225,400.00 - $418,600.00 USD base salary
Tools
RDF/OWL, knowledge graphs, graph databases, RAG
AI focus
Builds semantic and knowledge engineering capabilities for AI, including trusted AI, retrieval-augmented generation (RAG), semantic search, reasoning engines, AI-enabled knowledge management, and agentic AI.
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