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About Handshake
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Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50\), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full\-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.
Why join Handshake now:
- Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel
- Work hand\-in\-hand with world\-class AI labs, Fortune 500 partners and the world’s top educational institutions
- Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others
- Build a massive, fast\-growing business with billions in revenue
About the Role
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Handshake AI builds the training data that frontier labs use to push their models forward. Our Forward Deployed Engineering (FDE) team is a high\-leverage group of engineers who embed directly with our highest\-value customers, become experts in each customer’s specific needs, and build the bespoke solutions that win business and make engagements succeed. We’re hiring a Senior Product Manager to be the first PM embedded with this team. This is a highly entrepreneurial role: you’ll be designing the product function for FDE as much as running it.
A centerpiece of the role is off\-platform tasking: our customers often want work completed directly in their own tools and environments like lab\-built annotation surfaces, specialized research environments, and third\-party platforms we integrate with on their behalf. You’ll own that experience end to end, making it as seamless and trustworthy for our fellows to discover and access work on external surfaces, complete tasks, track time, get paid, and receive quality feedback. You’ll be the expert on each customer’s unique environment, and what it takes to make fellows successful on them.
You’ll embed with a customer, deeply understand their tooling and constraints, ship the solution that unlocks the engagement fast, and then help identify which of those solutions should graduate into the platform so the next ten customers get them out of the box. You’ll work across whatever our highest\-value customers need next, with the autonomy to move quickly and the visibility that comes with revenue\-critical work.
What You’ll Own
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- Customer\-embedded discovery and delivery \- Sit with our most important customers and their engineering teams, understand their tools, workflows, and constraints firsthand, and translate what you learn into solutions FDE can ship in days or weeks, not quarters.
- The off\-platform tasking experience \- The end\-to\-end journey of a fellow working in a customer’s environment: discovering and claiming work, getting access and credentials, completing tasks, tracking time, getting paid accurately, and receiving quality feedback.
- Bespoke\-to\-platform graduation \- Influence what solutions should generalize into platform primitives that make every future integration faster, turning FDE’s best one\-off solutions into durable product solutions.
- Goals, metrics, and tracking \- Define success metrics that measure speed and repeatability: time from a new customer need to a shipped solution, time from a new customer surface to first task live, fellow experience on external surfaces, and how much of each new engagement is served by existing product versus net\-new build.
- Cross\-functional partnership \- Work with FDE engineers on scoping and sequencing, with Operations on running customer projects at scale, with platform teams when bespoke work graduates into core product, and directly with customers as the product voice of the engagement.
Desired Capabilities
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- 5\+ years as a product manager shipping production code with engineering teams, ideally in customer\-facing, integrations, or platform contexts.
- Entrepreneurial and forward\-deployed by instinct: you’re energized by embedding with a customer, understanding their world firsthand, and building the thing that unlocks the deal without waiting for a playbook.
- Platform over one\-off mindset. You’ve built products where every customer looks different from the last, and you know the difference between shipping another bespoke solution and building a configurable system that handles needs nobody anticipated.
- Systems thinker. You can connect the dots across customer environments, worker experience, and platform infrastructure, spot the edge cases, and integrate them into coherent product decisions.
- Strong product instincts in ambiguous, fast\-iterating spaces. You can scope a problem from a customer conversation to a PRD to a shipped feature in hours, not days.
- Data\-informed but action\-oriented. You use data and customer signals to prioritize, but you trust user feedback and move quickly when the signal is clear.
Bonus Points
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- Experience as a PM (or forward deployed engineer) at a company known for embedding with customers (forward\-deployed, solutions, or professional\-services\-adjacent product work).
- Experience with human\-data, annotation, or AI training\-data workflows, or exposure to frontier\-lab data operations and tooling.
- Experience building integrations, browser extensions, or products that instrument work happening in third\-party software.
- Experience at a marketplace or gig platform where worker experience and marketplace integrity had to be balanced.
- 0 1 experience standing up new product surfaces inside a fast\-moving research\-adjacent org without a fully formed playbook.
We Offer
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Handshake delivers benefits that help you feel supported and thrive at work and in life.
*The below benefits are for full\-time US employees.*
Ownership: Equity in a fast\-growing company
Financial Wellness: 401(k) match, competitive compensation, financial coaching
Family Support: Paid parental leave, fertility benefits, parental coaching
Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend
Growth: $2,000 learning stipend, ongoing development
Remote \& Office: Internet, commuting, and free lunch/gym in our SF office
Time Off: Flexible PTO, 15 holidays \+ 2 flex days
Connection: Team outings \& referral bonuses
Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.
Compensation Range: $180K \- $220K
Salary Context
This $180K-$220K range is above the median for AI Product Manager roles in our dataset (median: $188K across 140 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 3,708 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Handshake, 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. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($200K) sits 7% below the category median. Disclosed range: $180K to $220K.
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.
Handshake AI Hiring
Handshake has 12 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, AI Software Engineer. Positions span San Francisco, CA, US, New York, NY, US. Compensation range: $170K - $416K.
Location Context
AI roles in San Francisco pay a median of $277,088 across 810 tracked positions. That's 27% above the national 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.
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