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About the job
About Us
In 2020, a group of senior technology and product experts from Google and Verily China decided to delve into the intelligent digitalization of life science clinical research. Their findings resulted in AlphaLife Sciences, a pioneer in the fusion of life sciences and AI computer science as an AI\-enabled integrated clinical research platform. Our flagship product, AuroraPrime, integrates Generative AI and Large Language Models (LLMs) into a powerful AI\-driven SaaS platform.
Trusted by global top MNCs, our innovations accelerate drug development and market entry. We are committed to globalizing AuroraPrime to enhance clinical trials and real\-world research by leveraging cutting\-edge AI, cloud computing, and big data. We help our clients achieve clinical operational efficiency, automate processes, and make smarter decisions to get their products to market faster.
We are proud partners with Microsoft's Pegasus Program, Google for Startups, and Johnson \& Johnson Innovation JLABS, delivering cutting\-edge solutions like Generative AI\-Copiloted Medical Writing, Intelligent EDC and Data Management, and Agile Trial Management.
The Role
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AlphaLife Sciences is seeking a Product Manager to develop and scale AI\-powered clinical applications that leverage generative AI and large language models (LLMs). You will focus on building practical, application\-layer AI solutions that streamline pharmaceutical workflows and extract insights to drive innovation in life sciences.
We're looking for a driven individual who thrives on ownership, enjoys tackling complex challenges, and can deliver results in a dynamic environment. You'll collaborate with a talented team of industry and technology experts to bring innovative AI solutions to the market.
If you're passionate about building exceptional products and enjoy tackling complex challenges with intuitive solutions, this opportunity could be ideal for you.
What You'll Do
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- Build comprehensive knowledge of clinical and regulatory workflows, document types, and industry best practices relevant to life sciences
- Engage with pharmaceutical clients, clinical teams, industry specialists, and AI/ML specialists to identify workflow pain points and translate them into scalable AI\-driven product capabilities
- Lead product feature development from conception through delivery, including requirements gathering, specification writing, and quality validation
- Create detailed product specifications using agile practices, informed by industry standards and user needs
- Drive feature roadmap decisions and maintain clear prioritization within your product domain
- Partner with Engineering, QA and cross\-functional teams to ensure high\-quality product delivery
- Design and enhance generative AI capabilities leveraging large language models (LLMs)
- Coordinate release cycles and development sprints to deliver valuable enhancements at optimal timing
Requirements
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- 3\+ years of experience in Product Management or comparable professional experience
- Experience contributing to the design and development of AI\-powered products leveraging large language models (LLMs), with a proven track record in product strategy, development processes, and execution
- Ability to conduct independent user interviews and user research to identify customer needs and product opportunities
- Strong drive to tackle complex business problems and create streamlined, scalable solutions
- Excellent communication skills in English (native or near\-native proficiency), with meticulous attention to detail
- Self\-motivated performer who excels in dynamic environments with evolving requirements
- Bachelor's degree required
- Must be authorized to work in the United States
Nice to Have
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- Experience or familiarity with pharmaceutical, biotech, or clinical research sectors. Familiarity with regulatory standards in life sciences (e.g., FDA, ICH)
- Experience using JIRA, Confluence, or other project management tools
- Familiarity with generative AI workflows, including prompt design, model evaluation, or AI\-assisted product features
What We Offer
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- Opportunity to work on breakthrough AI technology that accelerates patient access to treatments
- Collaborative environment with leading experts in AI and life sciences
- Professional development opportunities and mentorship
- Competitive compensation and benefits package
- Flexible work arrangements
AlphaLife Sciences is an equal opportunity employer and does not discriminate based on protected veteran status, disability, or other legally protected status. If you require a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please notify our recruiters at any stage of the process.
Please note: Applicants must be authorized to work in the United States without the need for current or future visa sponsorship. At this time, AlphaLife Sciences is unable to sponsor visas for applicants.
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 3,823 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Alpha Life Sciences, 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 $213,800 based on 583 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Alpha Life Sciences AI Hiring
Alpha Life Sciences has 1 open AI role right now. They're hiring across AI Product Manager. Based in Iselin, NJ, US.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, 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 $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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.
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