Director of Product
New
P
PrefectAutomation infrastructure
Location: Remote; Workplace: RemoteFull-TimeDirector
Salary$191K - $276K; $191K – $276K • Offers Equity; Multiple Ranges; San Francisco Bay Area & NYC Metro:: Base Salary $221K – $276K • Offers Equity; Washington D.C., Boston, LA Metro, Seattle:: Base Salary $200K – $257K • Offers Equity; Denver, Chicago, Atlanta, & all other U.S. metros:: Base Salary $191K – $238K
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Job Details
- Experience
- 10+ years in product
- Required Skills
- Product Management
Requirements
- Bring 10+ years of product experience.
- Have leadership-level product management experience.
- Have owned multi-team roadmaps and made difficult prioritization decisions.
- Have shipped products through others without direct authority over them.
- Have experience in start-ups and engineering-led organizations.
- Be able to influence product work without a product organization or reporting line over the people building.
- Bring experience synthesizing across domains; multi-product portfolios, platform/product tension, or post-acquisition integration experience is a strong signal.
- Have deep familiarity with the modern data stack, orchestration, or developer tools.
- Hands-on experience with agentic systems or MCP is a bonus.
- Have helped other people improve their product skills.
Responsibilities
- Own product cohesion across Dagster, Prefect, and FastMCP, including how the products fit together and where the portfolio is going.
- Build the product discovery practice through user conversations, customer signals, and problem validation.
- Set standards for discovery, facilitate it across product surfaces, and coach engineers to conduct user conversations.
- Partner with engineers to frame problems and ground product decisions in customer evidence.
- Coach product engineers to weigh evidence, talk to users, and decide what not to build.
- Design and own the system for measuring the success of shipped products.
- Define what success means and ensure honest post-launch validation.
- Feed post-launch learnings into future product decisions.
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