Director, Agentic Lab
At a glance
Director-level role at Novartis (Internal Careers for Acquired Entities). Remote, United States · full-time · $194,600–$361,400 base.
remoteroles summary, based on the employer's posting.
What you'll do
- Build and test early versions of agentic AI systems and automated workflows
- Compare foundation models, agent frameworks, orchestration options and developer tools
- Produce reusable prototypes, accelerators and implementation examples for the Agentic Factory
- Coordinate with engineering, product and architecture groups to move proven prototypes into production
- Set guidance for prompting, reasoning, memory, evaluation and observability, and coach AI engineers
What you bring
- A bachelor's or higher degree in computer science, AI, engineering or a related technical area
- At least seven years developing AI, machine learning or software solutions, including technical leadership
- Hands-on work with LLMs, RAG, vector databases, APIs, Python, cloud-native development and agent frameworks
- A solid software engineering foundation, including delivery of production-grade AI applications
Who this fits
This director-level position suits a technical leader who can collaborate across research, engineering and business teams and mentor AI engineers. Remote work is available within the United States, with possible legal-entity limits; the role includes ten percent travel. Relocation is not offered.
From the employer
Band
Level 6
Job Description Summary
#LI - RemoteReporting 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 to productionize successful prototypes.
- Define best practices for prompt engineering, reasoning strategies, memory architectures, evaluation, and observability.
- Contribute to enterprise standards, documentation, and reusable engineering patterns for AI agents.
- Mentor AI engineers and cultivate a culture of experimentation, innovation, and continuous learning.
Essential Requirements:
- Education: Bachelor's or advanced degree in Computer Science, Artificial Intelligence, Engineering, or a related technical discipline.
- 7+ years of experience building AI, machine learning, or software engineering solutions, including technical leadership experience.
- Hands-on expertise with 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 is determined based 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, life and 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, holidays and 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 tas.nacomms@novartis.com call +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
$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