AI Product Manager
$180,000–$210,000 year
RemoteCalifornia, United States or Arizona, United States
Job Summary
Own the product vision, strategy, and roadmap for a core vertical spanning detection logic, AI-driven decisioning, risk scoring, and alert workflows. Deeply understand how fraud and AML teams use current systems to identify friction and coverage gaps, then translate that into clear, incremental releases. Partner with engineering to scope, prototype, and ship rapidly, operating hands-on in early product discovery. Use AI relentlessly to automate workflows and build features end-to-end, owning Product, Design, and Engineering. Continuously gather input from customers and data to refine direction, while communicating strategy and tradeoffs clearly to leadership. Balance speed, accuracy, and trust in a regulated domain where every decision impacts real people.
Required Qualifications
- AI-native operator: You don't just talk about AI. You use it every day. You've automated meaningful parts of your own work, you're comfortable building in tools like Cursor and/or Claude Code, and you instinctively ask 'what would this look like if AI could handle it?' for every workflow you encounter.
- Builder mentality: You are energized by taking something from zero to one and iterating fast. You prototype, test, and learn quickly. You don't wait for permission, and you act with urgency. You are comfortable with ambiguity, and have insanely high agency.
- Systems thinker: You understand complex, workflow-heavy products. You've worked on systems where the logic layer matters, where configurability is a feature, and where getting the abstraction right is the difference between a platform and a one-off.
- Strong product athlete: Experience building and shipping complex software products. You operate from ambiguity to clarity to execution.
- Technical depth: Comfort working closely with engineers on system design, data flows, APIs, and product architectures. You don't need to code production software, but you think like an engineer when it matters, and you can build on your own when you need to move fast.
- Data-driven and evidence-rooted: You use data, experimentation, and metrics to guide direction. You follow your curiosity with data. Self-conviction is a starting point, but you gather evidence before committing.
- Curious, not defensive: You question everything but assume positive intent. When challenged, you shift from defensiveness to curiosity. You start from 'I don't know' and treat that as a strength.
- Clear communicator: You write things down. You build in public. You default to public channels, shared docs, and visible decisions over private conversations and closed-door meetings.
- SF or Bay Area preferred, with at least one day/week in office. Remote also possible but limited to the following U.S. states: AZ, CA, CO, GA, ID, IL, KS, MD, MA, NH, NJ, NY, NC, OH, OR, PA, RI, SC, TX, UT, VA, WA
Desired Qualifications
- Experience with fraud, AML, compliance, risk, or similar detection/decisioning domains is a plus, not a necessity.
- Bonus points if you have started a company of your own before.
- You have started a company before.
- Background in fintech.
- Prior experience as a designer, an engineer, a data analyst, or a technical PM.
- Comfort with broad scope and fast context-switching across multiple product areas.
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