Senior Product Manager
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Job Description
Senior Product Manager at Compound, building AI tools for financial advisors. Leading product lifecycle while collaborating closely with operations and engineering teams.
Responsibilities:
- Own execution across the product lifecycle: Partner directly with financial advisors and operations staff to deeply understand workflows, pain points, and opportunities
- Rapidly translate user needs into product improvements and new features
- Write clear specs that engineers can run with — not 40-page PRDs, but enough to ship confidently
- Make pragmatic, high-quality decisions with imperfect information
- Measure what matters — define success metrics, instrument features, and use data to iterate
- Collaborate across the team: Work closely with engineering to scope, prioritize, and ship — you'll be in the code reviews, not just the standups
- Handle light design work initially; partner with external design resources as needed until we build internal design capacity
- Communicate tradeoffs clearly to leadership — no jargon, just clear thinking
- Shape our AI-first roadmap: Contribute to defining how AI agents will transform wealth management
- Go deep on model evals, agent architecture, and production deployment of AI tools
- Help build our Copilot — a natural-language interface for advisors to query client context
Requirements:
- 2-5 years in a PM role (total experience 6-12 years)
- More hands-on IC than team lead or org-builder
- You've shipped real products to real users, not just roadmaps
- Sharp on financial concepts — you know what "alts" are, understand tax-loss harvesting vs. tax planning, and can speak the language
- Fintech or wealth management exposure is a strong advantage for ramp speed
- Strong interest in AI tooling and how it changes product development
- Comfortable being hands-on in modern tools — Figma, Claude Code, SQL, etc.
- You don't need to write production code, but you can read it and talk to engineers in their language
Benefits:
- Direct access — real customers, fast feedback loops, no layers between you and impact
- Small team, high ownership — 6 engineers today, growing to 16 over 18 months
- AI in production — opportunity to build and deploy AI tooling with rapid feedback loops, not just experiment
- Operators who build — our advisors and ops team are partners, not just stakeholders
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