Senior Product Manager I (PLG Onboarding)

Housecall Pro is dedicated to helping home service professionals streamline their operations and improve their lives. As a Senior Product Manager for the Product-Led Onboarding team, you will focus on developing AI-driven onboarding experiences and collaborate with feature PMs to enhance user engagement and satisfaction.

Responsibilities:

• 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

Requirements:

• 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...)
• 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 signal, and talk to customers directly; you can describe a specific customer's workflow from memory, not just a persona slide
• You hold a high bar for quality and can articulate why something is wrong — not just that it is
• You operate with high agency: you move from insight to testable artifact without waiting for permission or perfect information
• You're honest about what you don't know, direct with feedback, and genuinely curious about why things work the way they do