Director, Agentic Lab

Novartis AG; United States; Remote; USD 195,000 - 361,000; Full time

Benefits offered by this job

Health, life, and disability benefits

401(k) with company contribution and 1

Job summary

Novartis AG in the United States invites applications for a Director, Agentic Lab, who will lead the design, prototyping, and validation of next-generation AI agents and autonomous workflows. The role reports to the Executive Director, Agentic Architecture & Lab, and partners with AI Engineering and Platform teams to productionize successful prototypes.

This remote role in the U.S. may require up to 10% travel; relocation is not provided.

Qualifications

• Bachelor's or higher in CS/AI/Engineering or related field.
• 7+ years building AI, ML, or software solutions with leadership.
• Hands-on with LLMs, agent frameworks, RAG, vector databases, APIs, Python, and cloud-native development.
• Strong software engineering background with production-grade AI applications.
• Excellent communication and cross-functional collaboration.

Responsibilities

• Lead rapid prototyping and validation of agentic AI solutions.
• Evaluate foundation models, agent frameworks, orchestration technologies, and tooling.
• Develop reusable proofs-of-concept and reference implementations.
• Partner with engineering teams to productionize prototypes.
• Define best practices for prompt engineering, memory architectures, and observability.
• Contribute to standards, documentation, and reusable patterns.
• Mentor AI engineers and foster experimentation and learning.

Skills

LLMs

Agent frameworks

Python

Cloud-native development

Technical leadership

Education

Bachelor's or advanced degree in Computer Science/AI/Engineering or related field

Tools

Vector databases

APIs

Cloud platforms

Job description

Job Description Summary

#LI - Remote
Reporting to the Executive Director, Agentic Architecture & Lab, the Director, Agentic Lab leads the design, prototyping, and validation of next-generation AI agents and autonomous workflows. The role evaluates emerging AI technologies, develops reusable reference implementations, and partners with engineering teams to transition successful innovations into enterprise-scale capabilities.
This position can be based remotely anywhere in the U.S. (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. 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

Major Accountabilities

• Lead rapid prototyping and technical validation of agentic AI solutions and autonomous workflows.
• Evaluate foundation models, agent frameworks, orchestration technologies, and developer tooling.
• Develop reusable proof-of-concepts, accelerators, and reference implementations for the Agentic Factory.
• Partner with AI Engineering, Platform Engineering, Product, and Architecture teams toproductionizesuccessful prototypes.
• Define best practices for prompt engineering, reasoning strategies, memoryarchitectures, evaluation, and observability.
• Contribute to enterprise standards, documentation, and reusable engineering patterns for AI agents.
• Mentor AI engineers andcultivatea culture of experimentation, innovation, and continuous learning.

Essential Requirements:

• Education:Bachelor'sor advanced degree in Computer Science, Artificial Intelligence, Engineering, ora relatedtechnical discipline.

• 7+ years of experience building AI, machine learning, or software engineering solutions, including technical leadership experience.

• Hands-onexpertisewith LLMs, agent frameworks, RAG, vector databases, APIs, Python, and cloud-native development.

• Strong software engineering background with experience building production-grade AI applications.

• Excellent communication and collaboration skills with the ability to work across research, engineering, and business teams.

Desirable Requirements:

• Experience in pharmaceutical, healthcare, or other regulated industries.
• Experience building enterprise agentic AI platforms and developer ecosystems.

Novartis Compensation Summary:

The salary for this position is expected to range between $194,600 and $361,400 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, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status.

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 to perform the essential functions of a position, please send an e-mail to [e-mail] or call [phone] and let us know the nature of your request and your contact information. Please include the job requisition number in your message.

Salary Range

$194,600.00 - $361,400.00

Skills Desired

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