This role pays more than
85%
of similar roles. Most pay
$223,087–$294,125
— the shaded band above.
At the midpoint, this role pays about
$322k
versus about
$259k
for comparable roles.
Based on 240 similar postings.
Employer
About Novartis
Novartis is a global biopharmaceutical company that researches, develops, manufactures, and markets prescription drugs in areas including oncology, immunology, neuroscience, and cardiology. Industry: Biopharmaceuticals
Novartis currently has
26 open roles
on FindRole.
Listed pay typically runs
$194,600–$361,400
across 26 roles with salary data.
The Executive Director, Semantic and Knowledge Engineering leads the strategy, architecture, and implementation of the enterprise semantic layer and knowledge engineering capabilities powering NovaOS. Reporting to the VP of Applied AI, Data Science, and Commercial Intelligence, this leader builds a trusted, reusable knowledge foundation by connecting data, business concepts, ontologies, taxonomies, and AI agents to enable consistent reasoning and interoperability. The role involves developing governance for metadata management and quality standards while driving innovation in knowledge graphs, retrieval-augmented generation, semantic search, and reasoning engines. The successful candidate will utilize expertise in RDF/OWL, graph databases, and semantic web technologies to solve complex data integration problems. This position requires deep experience in enterprise information architecture to support generative AI and agentic AI within highly regulated industries like pharmaceutical or healthcare sectors.
Define and execute the enterprise strategy for semantic technologies, knowledge engineering, and knowledge graph capabilities.
Develop and govern enterprise ontologies, taxonomies, business vocabularies, and semantic models.
Design and implement an enterprise semantic layer to enable trusted AI and consistent analytics.
Embed semantic capabilities into NovaOS products and AI solutions in partnership with cross-functional teams.
Establish governance, metadata management, and quality standards for enterprise knowledge assets.
Drive innovation in retrieval-augmented generation (RAG), semantic search, and reasoning engines.
Build and lead a high-performing team of semantic engineers and ontology specialists.
What we're looking for
Bachelor's or advanced degree in Computer Science, Information Science, Artificial Intelligence, Data Science, Bioinformatics, or a related discipline.
10+ years of experience in semantic technologies, knowledge engineering, enterprise architecture, data management, or AI platforms, including leadership experience.
Deep expertise with ontologies, taxonomies, metadata, RDF/OWL, knowledge graphs, graph databases, and semantic web technologies.
Experience building enterprise semantic platforms that enable AI, analytics, search, and data interoperability at scale.
Exceptional leadership, executive communication, and cross-functional stakeholder management skills.
Experience applying semantic technologies to generative AI, agentic AI, RAG, and enterprise AI platforms (preferred).
Experience in pharmaceutical, healthcare, or other highly regulated industries (preferred).
Ontologies
Knowledge Graphs
RDF
OWL
Semantic Web
RAG
Generative AI
Agentic AI
Metadata Management
Graph Databases
Data Science
Machine Learning
Deep Learning
Data Governance
Statistical Analysis
Time Series Analysis