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About This Role
About airSlate
airSlate is a global SaaS technology company that develops no\-code workflow automation, electronic signature, and document management solutions. Our award\-winning products \- SignNow, pdfFiller, DocHub, altaFlow, Instapage, and US Legal Forms \- serve over hundreds of millions of users and more than one million customers worldwide, helping organizations of every size digitize processes, improve efficiency, and transform how they work.
We’re in an exciting phase of growth and transformation, with teammates in more than 20 countries across three continents and main hubs in the United States, Poland, Romania, Ukraine, and Philippines.
At airSlate, we’re building value for customers and a culture where growth and innovation go hand in hand. We’re looking for people eager to shape products, scale a company, and thrive in a fast\-moving environment.
### About the team:
AI Labs is airSlate's bet on what comes after the toolbox era of software. No backlog rituals, no six\-month roadmaps, no committees — small teams, weekly ship cycles, real users from day one. We build AI\-native products for the businesses that actually run the economy: the contractor booking your kitchen remodel, the dentist scheduling your cleaning, the 10\-person shop drowning in W\-9s and PDFs nobody designed for them. They've been stuck with decades\-old software. We're here to change that, fast.
### The opportunity:
For thirty years, software gave people toolboxes — edit this, sign that, file the other thing, one click at a time. AI lets us skip the toolbox entirely and hand people the *outcome*: taxes filed, contracts signed, staff onboarded, done. That's not an incremental upgrade. It's a chance to make our own products — and everyone else's — obsolete, fast. Whoever builds this first wins a category. We want it to be us, and we want it to be you.### The role:
You'll own an AI\-native product end to end — not manage a backlog, not shepherd someone else's roadmap. You work closely with AI Labs' product leader, who sets the broad direction, but everything from "who is this customer, really" to "why is this metric moving" to "ship it tonight" is yours. You'll have a small team of engineers who are good, fast, and looking to you to make the next six months feel like an adventure instead of a slog.
### What you'll do:
- Get obsessed with the customer. Talk to SMB owners, watch them work, mine the signal sitting in our millions of existing users — find the problem they actually have, not the one that's convenient for us.
- Run on hypotheses, not opinions. Form a sharp bet, design the test, read the result honestly even when it stings, move.
- Own the funnel and the money. Activation, conversion, retention, monetization — know the numbers cold and push them yourself.
- Turn mess into a thing worth building. Insight is cheap; a sharp, buildable product decision is not.
- Build alongside your engineers, not above them. Prototype with AI tools — v0, Cursor, Lovable, whatever's fastest — and fix your own interface instead of filing a ticket for it.
- Ship in days, not quarters. Idea to something real in front of a user in about a week. Then do it again.
- Bring the energy that makes people want to build with you. This is the job where "it's just a job" gets you replaced.
### Who you are:
- \~3–5 years building software products and shipping V1s that real customers actually used — SMB experience is a strong plus.
- Customer\-obsessed by instinct, not by training — you start from their problem, not our roadmap.
- AI\-native. You use these tools every day, not just on slide decks, and you have sharp instincts for what they can and can't do yet.
- You've run experiments that mattered — you can name the bet, the test, and what you learned when you were wrong.
- Curious and genuinely unafraid to be wrong in public. Fast learners who chase the question outrun people who protect their ego.
- A real nose for product — you can tell good from bad in five minutes, not five meetings.
- Hands\-on by default. Given the choice between a rough prototype and a strategy doc, you build the prototype.
- Fluent in growth and monetization — funnels, conversion, pricing, the levers that actually move a business, not just a metric.
- Hungry for freedom on new things — and ready to run with it the moment you get it.
### Fair warning on how we hire:
Before we talk about strategy, we're going to ask you to build something — a real prototype, a few hours of work, not a two\-week slog. If that sounds like an annoying hoop, this probably isn't your role. If it sounds like the most fun part of the interview, you're exactly who we're looking for.
### Why this and not somewhere else:
Startup speed and ownership, backed by a company with 100M\+ users, real infrastructure, and the resources to actually support what you build — plus direct access to leadership, because this hire is that important to us. You won't wait for permission. You'll build the thing, watch someone use it, and know within a week if you're onto something real.
What we offer
Flexible working environment \- Our teams operate across the globe. We value in‑person collaboration in our hubs, but we also embrace remote and hybrid working. You can work from one of our offices in the United States, Poland, Romania or Ukraine, or remotely from many countries.
Competitive compensation and stock options \- We offer salaries that reflect local market conditions and experience, plus a performance\-based bonus system and stock options so you share in the company’s growth.
Professional growth and learning \- We invest in your development through courses, conferences, and access to learning resources. We encourage career growth and internal mobility, supporting teammates who want to explore new opportunities within airSlate.
Health and well‑being \- We provide comprehensive benefits tailored to each country, including health coverage, wellness programmes and access to fitness options. We also dedicate quarterly company\-wide Mental Health Days, when everyone takes time off to rest and recharge.
Family‑friendly culture \- Family life is part of who we are, and we embrace it in many forms. From flexibility for parents to our airSlate Junior Club for kids, to company\-wide family days and our pet\-friendly approach, we’re committed to making work and life easier to balance.
Giving back \- We support charitable initiatives around the world through the airSlate Care programme. Our current focus includes humanitarian aid in Ukraine and other regions, matching employee donations and supporting causes chosen by our teams.
Open communication \- We encourage transparent dialogue at all levels. From team discussions to company\-wide Q\&A sessions with our CEO, we make sure everyone has the chance to be heard and to influence how we grow.
*It is airSlate's policy to comply with all applicable equal employment opportunity laws by making all employment decisions without unlawful regard or consideration of any individual’s race, religion, ethnicity, color, sex, sexual orientation, gender identity or expressions, transgender status, sexual and other reproductive health decisions, marital status, age, national origin, genetic information, ancestry, citizenship, physical or mental disability, veteran or family status or any other basis protected by applicable national, federal, state, provincial or local law. airSlate's policy prohibits unlawful discrimination based on any of these impermissible bases, as well as any bases or grounds protected by applicable law in each jurisdiction. If you need assistance or an accommodation during the application process because of a disability, it is available upon request. airSlate is pleased to provide such assistance and no applicant will be penalized as a result of such a request. Pursuant to relevant law, where applicable, airSlate will consider for employment qualified applicants with arrest and conviction records.*
Read our Recruitment Privacy Notice to Learn how we process your personal information.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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 airSlate, 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 $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.
airSlate AI Hiring
airSlate has 1 open AI role right now. They're hiring across AI Product Manager. Based in Remote, US.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
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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