Senior Product Manager I (PLG Onboarding)
Confirmed live in the last 24 hours
housecall
Job Description
Why Housecall Pro?
Help us build solutions that build better lives. At Housecall Pro, we show up to work every day to make a difference for real people: the home service professionals that support America’s 100 million homes. We’re all about the Pro, and dedicate our days to helping them streamline operations, scale their businesses, and—ultimately—save time so they can be with their families and live well.
While our headquarters are based in Denver, Colorado, our team spans the globe, with teammates across Brazil, Poland, the Philippines, Mexico, and beyond. We care deeply about our customers and foster a culture where our company, people and Pros grow and succeed together—no matter where they’re based. Leadership is as focused on growing team members’ careers as they expect their teams to be on creating solutions for Pros.
We also offer:
- A generous benefits program that supports the whole you with medical, dental, vision, life, disability, and 401(k)
- Paid holidays and flexible, take-it-as-you-need-it paid time off
- Monthly tech reimbursements
- A culture built on innovation that values big ideas, no matter where they come from
- Equity in a rapidly growing startup backed by top-tier VCs
As a Sr. PM for our Product-Led Onboarding team with a strong focus on AI/agentic onboarding, you will be responsible for the platform-level onboarding experience, and will partner closely with feature PMs to enable and improve feature-specific onboarding experiences. The work is a mix of AI-native product development and deep workflow thinking about how field service businesses actually operate.
Our team is passionate, empathetic, hard working, and above all else focused on improving the lives of our service professionals (our Pros). Our success is their success.
What you do Each Day
- Set direction for your product area — using AI to accelerate synthesis and scenario planning, but owning the judgment calls on what to build, what to skip, and why
- Define the right problems — triangulating across usage and adoption data, AI-aggregated customer signal, and direct observation to identify what's actually broken, for whom, and why it matters
- Develop AI-first solutions — evaluating the full workflow before proposing a fix, with an active and specific eye toward where AI creates compounding value, and the discipline to recognize when it doesn't
- Build experiences customers trust — designing failure paths with the same rigor as success paths, specifying how AI behaves autonomously versus when it hands back to a human, and defining the quality bar before anything ships
- Measure what matters — connecting outcomes to customer and business impact, owning evaluation criteria for AI-powered features, and tracking what actually moved rather than what launched
- Execute through the triad — arriving with a prototype built with AI tools, writing minimal precise specs, and shipping with accountability for outcomes
Qualifications
- 5-7 years of experience in product management, ideally in vertical SaaS or fintech
- Bachelor’s degree or equivalent work experience required
- Proven experience shipping AI-powered features and defining rigorous quality standards for them; experience building agents preferred
- Advanced proficiency in data synthesis and experimentation frameworks
- Demonstrated ability to leverage AI prototyping tools to communicate and validate concepts (i.e. Cursor, Claude, v0...)
What will help you succeed in this role
- You've shipped AI-powered features and can describe how you defined quality, designed for failure modes, and measured whether the AI was actually working — not just that it launched
- You build with AI coding tools yourself — you've used v0, Cursor, Claude, Bolt, or similar to prototype ideas before involving engineering, and you treat that as part of how you think, not just how you communicate
- You can write an eval — you know how to define success criteria for AI behavior, enumerate what failure looks like, and produce test cases specific enough that a teammate could run them next week
- You triangulate — you pull and interpret usage data, use tools that aggregate customer signa
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