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### Summary
Location: Cambridge USA;
\#LI\-Hybrid 3 days/week in office
Internal job title: Associate Director, Agentic AI Solutions Product Manager
About the Role:
We are seeking a Product Manager Agentic AI Solutions to lead the product strategy, development, and enterprise integration of a portfolio of Agentic AI solutions supporting our Research organization. This role sits at the intersection of product management, AI platform strategy, research informatics, enterprise architecture, and governance, with a strong focus on solutions built on Palantir Foundry and AIP.
The ideal candidate will shape and scale AI products that accelerate scientific workflows, enable trusted human\-AI collaboration, and align with enterprise standards for agent interoperability, identity, security, and responsible AI adoption.
### About the Role
Key Responsibilities:
- Lead product management for multiple Agentic AI solutions serving the Research organization, from strategy and roadmap through execution, adoption, and lifecycle management.
- Define product vision, value proposition, and success metrics for AI\-enabled solutions that improve research productivity, decision support, and operational effectiveness.
- Partner with scientific, digital, data, engineering, platform, and business stakeholders to identify high\-value use cases and translate them into scalable product capabilities.
- Own product planning and prioritization for solutions built on Palantir Foundry and AIP, ensuring alignment with research needs and enterprise architecture standards.
- Lead integration efforts between Research Agentic AI products and the Enterprise Agentic Mesh, enabling interoperability, orchestration, and scalable agent\-to\-agent collaboration.
- Develop the strategy for integrations with other enterprise agents and shared AI services, ensuring cohesive user experiences and reusable patterns across the organization.
- Define and drive the product strategy for Agentic Identity and Security, including trusted access models, authorization approaches, auditability, governance, and risk\-aware deployment practices in partnership with security and platform teams.
- Establish frameworks for agent lifecycle management, product governance, release planning, and operational readiness.
- Work closely with engineering and architecture teams to define requirements for APIs, data products, orchestration patterns, observability, and system integration.
- Partner with legal, compliance, privacy, cyber, and risk stakeholders to support responsible and compliant deployment of Agentic AI capabilities; Act as a thought partner to senior leadership on the evolving role of Agentic AI in Research and the broader enterprise.
- Create business cases, product roadmaps, and executive communications that clearly articulate priorities, dependencies, risks, and expected outcomes.
- Monitor product performance, user adoption, and business impact, using insights and feedback loops to continuously improve products and platform strategy.
- Drive cross\-functional operating models and ways of working across product, engineering, data, and research stakeholders in a complex enterprise environment.
Essential Requirements:
- Bachelor’s degree required; advanced degree preferred in life sciences, computer science, engineering, data science, business, or a related field.
- 10\+ years’ experience in product management, with experience operating at a strategic level across complex, enterprise\-scale technology products.
- Strong experience working with AI, machine learning, generative AI, or agentic systems in a product, platform, or transformation capacity.
- Experience with Palantir Foundry and or AIP.
- Strong understanding of enterprise product delivery, platform operating models, and integration strategy.
- Experience leading cross\-functional initiatives involving business, technical, architectural, and governance stakeholders, with demonstrated ability to manage multiple products or workstreams simultaneously in a matrixed global organization.
- Familiarity with research and development environments in pharma, biotech, or life sciences.
- Strong communication, stakeholder management, and executive presentation skills.
- Proven ability to translate ambiguous business needs into clear product direction and actionable roadmaps.
Desirable requirements:
- Understanding of identity, access, security, and governance concepts for enterprise AI systems preferred.
The salary for this position is expected to range between $138,600 and $257,400 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.
To learn more about the culture, rewards and benefits we offer our people clickhere.
Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people\-and\-culture
Benefits and Rewards: Learn about all the ways we’ll help you thrive personally and professionally.
Read our handbook (PDF 30 MB)
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 \& 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 \[email protected] or 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.
Division
Biomedical Research
Business Unit
Research
Location
USA
State
Massachusetts
Site
Cambridge (USA)
Company / Legal Entity
U175 (FCRS \= US175\) Novartis Institutes for BioMedical Research, Inc.
Functional Area
Research \& Development
Job Type
Full time
Employment Type
Regular
Shift Work
No
Salary Context
This $138K-$257K range is above the median for AI Product Manager roles in our dataset (median: $190K across 108 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 2,799 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Novartis, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills in Demand for This Role
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $211,000 based on 454 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $159,385. This role's midpoint ($198K) sits 6% below the category median. Disclosed range: $138K to $257K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $252,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,760; Mid: $159,385; Senior: $227,500; Director: $242,000; VP: $250,000.
Novartis AI Hiring
Novartis has 3 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer. Positions span Cambridge, MA, US, East Hanover, NJ, US. Compensation range: $257K - $361K.
Location Context
Across all AI roles, 16% (460 positions) offer remote work, while 2,318 require on-site attendance. Top AI hiring metros: New York (2,241 roles, $208,300 median); San Francisco (1,822 roles, $252,000 median); Los Angeles (1,611 roles, $188,900 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 2,799 open positions tracked in our dataset. By seniority: 98 entry-level, 1,283 mid-level, 1,092 senior, and 326 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (460 positions). The remaining 2,318 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $252,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 30 roles); AI Safety ($274,200 median, 43 roles); Research Engineer ($260,000 median, 387 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 2,799 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (1,978), AI Software Engineer (197), Data Scientist (195). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (98) are outnumbered by mid-level (1,283) and senior (1,092) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 326 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (460 positions), with 2,318 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,000. Top-quartile roles start at $252,000, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,433 postings), Aws (840 postings), Rag (663 postings), Azure (639 postings), Gcp (537 postings), Pytorch (445 postings), Prompt Engineering (418 postings), Claude (396 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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