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About This Role
Revvity
Revvity is a developer and provider of end-to-end solutions designed to help scientists, researchers, and clinicians solve the world’s greatest health challenges. We pair the enthusiasm of an industry disruptor with the experience of a longtime leader. Our team of 11,000+ colleagues from around the globe are vital to our success and the reason we’re able to push boundaries in pursuit of better human health.
Find your future at Revvity.
Director of Development, AI Native
Overview:
Revvity Signals makes market-leading software that empowers scientists across Life Science R&D, clinical research, and specialty chemicals to make better medicines and products, faster. Our flagship offering is the SaaS Signals Research Platform that provides knowledge capture, collaboration, analysis and visualization tools across the full depth and breadth of scientific discovery workflows. The viral adoption of our software is accelerating innovation, expediting drug development for a healthier world and facilitating the creation of sustainable materials. Join us as a Director of Development, AI Natives, where you will manage the development of AI native product(s). This is your chance to build and manage a high-performance team and product to shape the future of AI-driven Life Sciences applications.
Main functions:
- A proven background in software architecture and design patterns to develop a greenfield AI software application.
- Strategic leadership capabilities to translate the business and GTM requirements into a modern technical architecture.
- Detailed knowledge and hands-on experience with AWS, GCP and Azure infrastructure, software and AI services.
- A complete understanding of DevSecOps philosophy in software design and development including CI/CD, testing, and observability. (deploy at will - fail with grace)
- Expert proficiency in cloud native design (containers, microservices, APIs)
- Strong understanding of scale, performance optimization, and building durable software that drives growth.
- Collaborate with cross-functional teams to prioritize integration with other Signals products and to identify the development of common platform services that can be used across Revvity platform.
Responsibilities:
- Experience in modern programming languages, LLMs and the use of AI code tooling (Go, Python, Java, Claude, CoPilot, etc)
- Experience leading cross functional teams and mentoring engineers
- Work closely with UX and product management to understand product features and how they fit into the overall product experience. Revvity Proprietary Information
- Participate in all team building activities such as hiring, planning, requirements definition, design discussions, code reviews, and software development.
- Work effectively with other teams such as PM, QA, Cloud Ops, and SRE’s to build and deploy a quality product for our customers.
Basic Qualifications:
- BS/MS Computer Science or equivalent
- Minimum 12+ years of experience and at least 10 years’ experience as a manager
Preferred Qualifications:
- Advanced Degree preferred
Experience with ChemBioInformatics preferred.
- Proven experience in designing and implementing AI infrastructure including building applications powered by LLMs.
- Expert programming skills in Python and Java
- Proven experience with distributed execution frameworks like Dask, Sparc, Ray, or similar • Subject matter expert in emerging technologies and trends in areas such as: Artificial Intelligence (AI) & Machine Learning (ML), Cloud Computing, Data Science, Big Data, and Cyber Security
- Proven Experience with AWS
- Expert building large scale, high-available applications desired.
- Experience as a full stack developer a plus.
- Experience with open source technologies.
- Excellent verbal and written communication skills required
- Must be able to communicate effectively with other team members
- Creative problem-solving skills
What do we offer?
We provide competitive and comprehensive benefits to our employees. Below are some highlights of our benefits:
- Medical, Dental, and Vision Insurance Options
- Life and Disability Insurance
- Paid Time-Off
- Parental Benefits
- Compassionate Care Leave
- 401k with Company Match
- Employee Stock Purchase Plan
Learn more about Revvity’s benefits by visiting our Bswift (opens in new window) page. Log-In instructions are provided towards the bottom of the Bswift page.
For benefit-eligible roles only. Part-time and temporary roles may not be eligible for all benefits listed. Please reach out to your recruiter for more information.
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Please remember:
We will never ask you to pay for an interview, job offer, equipment, training, or any part of our recruitment process. Always verify that recruitment emails come from our official company email domain (revvity.com). Revvity will never conduct interviews via text message, messaging apps, or social media direct messages. If you're ever unsure whether a recruitment message is genuine, please contact us through our official careers website before responding.
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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 9,079 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Revvity, 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 Required
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 $220,200 based on 947 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,300.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Revvity AI Hiring
Revvity has 2 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer. Positions span Concord, NH, US, Thane, Maharashtra, India.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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