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About This Role
Product Manager – AI Platform \& Product Adoption (Greenfield Initiative)
Location: Irvine, CA (Hybrid: Onsite Monday–Thursday, Remote Fridays)
Type: Contract\-to\-Hire
Compensation: $50\-60 an hour
About the Opportunity
We are building something that has never existed before.
As part of a brand\-new AI division, we're developing an intelligent platform that will transform how a global workforce is managed, scheduled, and supported through AI. This greenfield initiative represents one of the largest technology investments in the company's history and will fundamentally reshape business operations for years to come.
We're looking for a Product Manager who is passionate about launching products that people actually use. This role sits at the intersection of Product, Engineering, Design, and Business Operations, ensuring new features are successfully introduced, adopted, and continuously improved.
If you enjoy working closely with users, translating business needs into product improvements, and helping organizations embrace new technology, this is an opportunity to make an enterprise\-wide impact while helping define a product from the ground up.
What You'll Do
As a Product Manager, you'll own the successful rollout and adoption of new capabilities across our AI platform. You'll partner with engineering teams building the product while working directly with business leaders and end users to ensure every release delivers measurable value.
Product Launch \& Adoption
- Lead the rollout of new product features across the organization, ensuring successful adoption by business users.
- Develop launch strategies, communication plans, and rollout timelines.
- Drive change management efforts to ensure smooth transitions as new functionality is released.
Product Enablement
- Deliver live product demonstrations, workshops, and training sessions.
- Create documentation including user guides, release notes, FAQs, and training materials.
- Act as the product expert for business stakeholders, providing ongoing guidance and support.
Customer \& Business Partnership
- Build strong relationships with business leaders and operational teams.
- Gather user feedback, identify pain points, and understand evolving business needs.
- Translate feedback into actionable product enhancements for Engineering.
Cross\-Functional Collaboration
- Partner daily with Product, Engineering, Design, QA, AI/ML, and Operations teams.
- Participate throughout the product lifecycle, from planning and validation through launch.
- Help prioritize improvements based on customer impact and business value.
Continuous Improvement
- Monitor product adoption, usage trends, and customer feedback.
- Identify opportunities to improve workflows, user experience, and operational efficiency.
- Measure product success using adoption metrics and user engagement.
What You Bring
- 3\+ years of experience in Product Management, Product Operations, Business Analysis, Customer Success, or similar customer\-facing product roles.
- Experience launching software products or leading feature rollouts.
- Strong presentation and communication skills with the ability to explain technical concepts to non\-technical audiences.
- Experience gathering business requirements and translating them into clear product recommendations.
- Ability to build relationships across Engineering, Product, Operations, and executive stakeholders.
- Excellent organizational and project management skills with the ability to manage multiple initiatives simultaneously.
- Experience working with tools such as Jira, Confluence, Microsoft Teams, or similar collaboration platforms.
Preferred Qualifications
- Experience working in Agile or Scrum environments.
- Familiarity with the Software Development Lifecycle (SDLC).
- Experience creating release notes, user documentation, and training content.
- Understanding of UI/UX principles and user\-centered product design.
- Experience measuring product adoption and using customer feedback to influence product direction.
- Experience supporting enterprise software or large\-scale internal platforms.
Our Technology Stack
While this is not a hands\-on engineering role, you'll work closely with teams building modern cloud\-native applications using:
- React \& Redux
- Java (Spring Boot)
- Python \& AI/ML frameworks
- AWS
- Docker
- Kubernetes
- Helm
- PostgreSQL \& SQL
- Domo
Why This Role Is Exciting
Greenfield Product
Help define and launch a brand\-new AI platform from day one—without legacy systems or existing processes slowing you down.
Enterprise Scale
Startup Autonomy, Fortune 100 Stability
Operate like an early\-stage startup while backed by one of the world's largest and most financially stable organizations.
Highly Collaborative Team
Work alongside AI/ML Engineers, Backend Engineers, Frontend Engineers, QA, DevOps, BI Analysts, Product Designers, and Business Leaders to build products that solve real\-world problems.
High Visibility \& Growth
This initiative is one of the company's top strategic priorities, giving you direct visibility into executive leadership and significant opportunities for long\-term career growth.
Salary Context
This $104K-$124K range is in the lower quartile 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 Match Made Tech, 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. This role's midpoint ($114K) sits 47% below the category median. Disclosed range: $104K to $124K.
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.
Match Made Tech AI Hiring
Match Made Tech has 1 open AI role right now. They're hiring across AI Product Manager. Based in Los Angeles, CA, US. Compensation range: $124K - $124K.
Location Context
AI roles in Los Angeles pay a median of $215,000 across 397 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.
Frequently Asked Questions
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