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### Summary
Head Clinical Development AI \& Technology
Primary Location: London, United Kingdom
Other Locations: Dublin, Ireland; Basel, Switzerland; United States
Relocation Support: Yes
Lead the design and execution of a scalable, enterprise\-aligned technology, data, and artificial intelligence strategy for Clinical Development. As Head Clinical Development AI \&Tech you will architect and operationalize advanced digital platforms, analytics ecosystems, and artificial intelligence and generative artificial intelligence capabilities to optimize end\-to\-end clinical development execution from study design through submission. Working at the intersection of clinical science, data engineering, and platform technologies, you will drive integration of structured and unstructured data assets, industrialize artificial intelligence use cases tied to key scientific questions, and ensure compliant, high\-performance systems that accelerate evidence generation, optimize delivery, and enable real\-time, data\-driven decision\-making at global scale.
### About the Role
Key Responsibilities
- Define and execute end\-to\-end technology, data, and artificial intelligence strategy for Clinical Development
- Act as strategic advisor to senior leadership on digital transformation, automation, and data modernization
- Deep ecosystem engagement to proactively identify emerging trends and translate them into iterative, impact\-driven plans that accelerate Clinical Development
- Lead delivery of scalable platforms and artificial intelligence solutions across all clinical development capability areas
- Oversee product roadmaps, lifecycle governance, vendor partnerships, and platform performance
- Drive identification, prioritization, and industrialization of artificial intelligence and generative artificial intelligence use cases with measurable impact
- Integrate analytics, automation, and diverse data assets to enable seamless end\-to\-end clinical workflows
- Ensure compliance with good clinical practice, data privacy, cybersecurity, and regulatory standards globally
- Establish robust governance frameworks, operating models, and cross\-functional collaboration structures
- Lead global, matrixed teams across technology, data science, engineering, and platform leadership
- Drive continuous improvement in delivery quality, release management, and operational resilience
Essential Requirements
- Advanced degree in Technology, Data Science, Engineering, or Life Sciences or equivalent experience
- Minimum 10 years of leadership experience within global, matrixed environments in regulated industries such as pharmaceuticals or healthcare
- Deep expertise in clinical development processes and supporting technology platforms across the full development lifecycle
- Proven experience designing and scaling artificial intelligence and machine learning solutions in regulated environments
- Strong knowledge of data architecture, cloud technologies, and enterprise\-scale digital platform implementation
- Demonstrated ability to lead multidisciplinary teams across technology, data science, and engineering functions
- Strong understanding of regulatory requirements including good clinical practice, data privacy, and data integrity standards
- Excellent communication and stakeholder engagement skills with the ability to translate complex technical concepts clearly
Desirable Requirements
- Master of Business Administration or equivalent leadership qualification
- Experience leading large\-scale organisational transformation and artificial intelligence\-driven change management initiatives
The salary for this position is expected to range between $ 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 click here.
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
Development
Business Unit
Development
Location
USA
State
New Jersey
Site
East Hanover
Company / Legal Entity
U014 (FCRS \= US014\) Novartis Pharmaceuticals Corporation
Functional Area
Data and Digital
Job Type
Full time
Employment Type
Regular
Shift Work
No
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 3,708 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 $216,175 based on 270 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; 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 East Hanover, NJ, US, Remote, US. Compensation range: $361K - $418K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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