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Senior Product Manager, AI
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Mitratech Legal Solutions builds the software the world's largest corporate legal, risk, and compliance teams run on—managing legal matters, reviewing outside\-counsel spend, generating contracts and documents, and running legal holds and compliance obligations. We are now putting AI at the center of that work: automating the manual review that consumes legal teams, drafting and assembling documents, and surfacing the status, risk, and key facts of a matter the moment someone needs them.
It's hard, high\-stakes work—the output has to be accurate, defensible, and dependable at enterprise scale—and it is done by strong product, engineering, and design people. For over 35 years, Mitratech has served 20,000 organizations worldwide, including 30% of the Fortune 500 and more than 500,000 users across 160\+ countries.
If this is the kind of problem you want to work on, we'd like to meet you.
Job Overview
As a Senior Product Manager on our AI team, you will own a significant part of Mitratech's AI program and drive it from concept to production and general availability. You will work across the AI fabric—the shared platform our products build on—and the experiences customers use on top of it, partnering closely with engineering, design, and fellow product leaders. This is a high\-ownership role on a senior team: you take on ambiguous, high\-stakes problems, decide what matters most, and are accountable for outcomes that hold up at enterprise scale. The exact area you own will be shaped to your strengths and to where the need is greatest.
Job Description
### Essential Duties \& Responsibilities
- Own a meaningful area of Mitratech's AI program end to end—from strategy and roadmap through delivery to production and general availability against committed dates.
- Turn ambiguous, high\-stakes problems into clear plans and shipped outcomes, deciding what matters most and driving decisions to closure.
- Partner closely with engineering on an AI\-dense platform to convert discovery into shipped scope, eliminating the gap between plans and delivery.
- Translate customer and early\-access feedback into a clear, prioritized view of what to build next.
- Keep solutions coherent and reusable across the shared AI platform and the experiences built on top of it, rather than one\-off per product.
- Represent the product with senior stakeholders and customers, and raise the bar for product craft across the team.
### Requirements \& Skills:
- 7\+ years of product management experience, including building AI/ML or technically deep platform products.
- Proven track record of shipping complex products to general availability on committed timelines in an engineering\-intensive environment.
- Ability to own ambiguous, cross\-cutting problems independently and drive them to shipped outcomes.
- Working fluency with generative AI and large language model product concepts, and comfort operating close to engineering and architecture.
- Strong cross\-functional leadership across engineering, design, and product, with clear written and verbal communication to senior stakeholders.
- Enterprise B2B SaaS experience, ideally serving legal, risk, compliance, or other regulated functions.
### Education:
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- An advanced degree (e.g., MBA or a technical master's) is a plus.
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 Mitratech, 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.
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.
Mitratech AI Hiring
Mitratech has 2 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer. Positions span Austin, TX, US, Remote, US. Compensation range: $220K - $220K.
Location Context
AI roles in Austin pay a median of $214,343 across 87 tracked positions.
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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