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Salary
$225k – $419k per year
Location
Remote (United States)
Seniority
Architect · 10+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Novartis is a Swiss multinational pharmaceutical company dedicated to the research, development, and manufacturing of innovative medicines. The organization focuses on addressing high-unmet patient needs across key therapeutic areas, including oncology, immunology, neuroscience, and cardiovascular-renal-metabolic diseases. Through its advanced technology platforms - such as gene and cell therapy, radioligand therapy, and xRNA - the firm aims to reimagine medicine to improve and extend lives worldwide.

Band

Level 7

Job Description Summary

#LI-Hybrid

Reporting to the VP, Applied AI, Data Science, and Commercial Intelligence, the Executive Director, Semantic and Knowledge Engineering leads the strategy, architecture, and implementation of the enterprise semantic layer and knowledge engineering capabilities that power NovaOS. This role is responsible for creating a trusted, reusable knowledge foundation that connects data, business concepts, ontologies, taxonomies, and AI agents to enable consistent reasoning, interoperability, and scalable enterprise intelligence.

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.

Job Description

Key Responsibilities:

  • Define and execute the enterprise strategy for semantic technologies, knowledge engineering, and knowledge graph capabilities.

  • Lead the development and governance of enterprise ontologies, taxonomies, business vocabularies, and semantic models thatestablisha shared understanding across the organization.

  • Design and implement the enterprise semantic layer that enables trusted AI, consistent analytics, interoperability, and reusable business knowledge.

  • Partner with Applied AI, Data Science, Product Management, Engineering, and Business teams to embed semantic capabilities intoNovaOSproducts and AI solutions.

  • Establish governance, metadata management, knowledge lifecycle processes, and quality standards for enterprise knowledge assets.

  • Drive innovation in knowledge graphs, retrieval-augmented generation (RAG), semantic search, reasoning engines, and AI-enabled knowledge management.

  • Build and lead a high-performing team of semantic engineers, ontology specialists, and knowledge engineers while fostering technical excellence and innovation.

Essential Requirements:

  • Education:

    • Bachelor'sor advanced degree in Computer Science, Information Science, Artificial Intelligence, Data Science, Bioinformatics, ora relateddiscipline.
  • 10+ years of experience in semantic technologies, knowledge engineering, enterprise architecture, data management, or AI platforms, including leadership experience.

  • Deepexpertisewith ontologies, taxonomies, metadata, RDF/OWL, knowledge graphs, graph databases, semantic web technologies, and enterprise information architecture.

  • 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.

Desirable Requirements:

  • Experience applying semantic technologies to generative AI, agentic AI, RAG, and enterprise AI platforms.
  • Experience in pharmaceutical, healthcare, or other highly regulated industries.

Novartis Compensation Summary:

The salary for this position is expected to range between $225,400 and $418,600 per year.

The final salary offered isdeterminedbased on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors.

Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.

US-based eligible employees will receive a comprehensive benefits package that includes health,lifeand disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days,holidaysand other leaves.

EEO Statement:

The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. We strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential.

Accessibility and reasonable accommodations

The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or in order to perform the essential functions of a position, please send an e-mail to [email protected] +1 (877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.

https://www.novartis.com/careers/careers-research/notice-all-applicants-us-job-openings

Salary Range

$225,400.00 - $418,600.00

Skills Desired

Artificial Intelligence (AI), Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Visualization, Deep Learning, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Mentorship, Stakeholder Engagement, Statistical Analysis, Time Series Analysis
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