The RoleThis is the most senior individual contributor seat in Product, with no direct reports. You'll work as a peer to the leaders of Ops, Data, Design, and Engineering.
Senior Product Managers here each own a workstream inside one of four swim lanes. You drive the Service Experience product agenda end to end: everything after a customer books, for customers and Pros, and the AI increasingly behind it. Two jobs at once: a critical thought partner to leadership on how AI reshapes our service experience, and an operator who ships with peers in engineering, design, data, marketing, and ops at a speed and quality that most would not believe. You're accountable for company-level numbers, not initiative-level ones.
What makes this role different:- Thought partner, not order-taker. Leadership wants your view on where AI takes the service experience, and expects you to change their minds sometimes.
- Speed and quality together. Small team, peers in engineering, design, data, marketing, and ops who move fast, and few layers between your judgment and what ships.
- Ultra AI-forward is the point. We want someone already operating the way most PMs will operate in five years.
- Strategy and hands. You still prototype with LLMs, write eval sets, read transcripts, and re-architect live systems yourself.
RequirementsWhat You'll Own- The Service Experience swim lane's product strategy and roadmap: marketplace trust after booking, including setting the right expectations on both sides, steering Pros toward great work, and the increasingly AI-assisted policies that arbitrate conflicts.
- AI-powered support for customers and Pros, including the eval systems that gate every change (golden datasets, automated judges, regression detection, human-review sampling).
- Two company-level numbers: Contribution LTV (profit per customer over their lifetime) and the brand-promise metrics.
- The vision and proof of concept for how AI transforms the customer and Pro experience, not just support.
- The bar for product: standards for shipping trustworthy AI, influencing Senior PMs by showing what great looks like, and being the person leadership calls for the hardest two-sided judgment calls.
Problems to SolveMaking AI support provably good, then letting it do a lot more. AI handles roughly a third of customer support conversations today. The goal for the next year: over half of all inquiries, customer and Pro, resolved with high satisfaction. Getting there is gated on one hard, ongoing, technical thing: proving the AI resolved a case rather than just closed it. That means defining "good" for an open-ended conversation, and catching quality drift before a customer or Pro feels it. You'll build Pro-side support on that foundation: unglamorous work that makes a slick demo safe to scale.
Keeping the promise on both sides. Most service failures aren't bad work, they're mismatched expectations: the grass grew a tier past what was booked, or the customer wants a date the Pro can't commit to. Our promise is priced as quoted, done right, and keeping it means getting expectations right before the work starts and steering Pros toward great work. These aren't bad actors: both sides are right from where they sit, and the marketplace has to make a call. You'll build the policies and the increasingly AI-assisted systems that decide fairly and consistently at scale, and make the judgment call yourself when there's no clean answer.
Making every customer more profitable. Trust isn't a soft metric here: customers who get what they were promised stay for years, and conflicts resolved fairly cost less to serve. You'll own Contribution LTV, targeting +10% year over year. The hard part is knowing which lever moves it (retention, cost to serve, fewer make-goods) and proving the attribution, not just asserting it.
Deciding what AI does to the whole experience, not just support. AI already runs quietly in pricing, fraud detection, and routing. The next unlock is AI that customers and Pros notice. By year one, we want a working proof of concept and a leadership-endorsed vision for how AI transforms that experience. What's first? How do you know?
What Success Looks Like (Year 1)- 50%+ of support inquiries resolved by AI with high customer and Pro satisfaction, behind an eval suite blocking regressions, plus a first version of Pro-side AI support live.
- Contribution LTV up 10% year over year, with attribution you can defend.
- Brand-promise metric goals hit: priced as quoted, done right.
- A working proof of concept and a leadership-endorsed vision for how AI transforms the customer and Pro experience.
- Leadership treats you as the person who defines where the service experience goes, not just delivers it, and the team ships faster and better because you're in the room.
Who You AreA track record of extraordinary outcomes. Not solid, exceptional: results with your fingerprints on the decision. A generically solid resume, or wins you can't explain, won't clear the bar.
Obsessed with AI, to the point of building. You use AI daily, have built with LLMs, and reach for AI before asking a person when you need data or want to read code. You have real intuition for whether an AI experience is good, and a view on where it's headed. Unlikely to be a good fit if you treat LLM quality as a vibe check, or evals as engineering's problem.
Obsessed with the customer and the Pro. You live in transcripts and Pro feedback to understand both sides, and hold their interests at once, with a rationale you'd defend to either, neither indecisive nor a hip-shooter. Skip this one if you think you already know what our customers and Pros need.
Ruthlessly data-driven. You find root causes through data, and reach for the number before the opinion. What doesn't work: leading with your gut, or refusing to move until the data is perfect.
Unbelievable speed, without dropping quality. You ship scrappy, compress timelines, and it still makes you proud. You dive into unglamorous details like labeling eval sets and rewriting policy, because that's what quality costs. This won't work if perfectionism keeps you from shipping, or your speed leaves a mess behind.
A thought partner who multiplies the room. You change leadership's mind, raise the bar for PMs by doing the work, and influence peers who don't report to you. Unlikely to be a good fit if you wait for direction, or guard what you know.
This Role Is NOT- A people-management role. You're an individual contributor with no direct reports. Influence comes from judgment and output, not a team you manage.
- A support PM role. Support is one surface of a broader area covering trust and AI, not a ticket queue or a help center.
- The internal-AI tooling role. A separate effort drives AI adoption in internal tooling. This role is about AI in the experience customers and Pros have.
- A strategy-only seat. You'll write evals, read transcripts, and prototype with LLMs. If you'd rather just set direction, this will frustrate you.
- A tactical delivery role. This one owns where the service experience goes, not the next feature in it. If you're strongest turning someone else's strategy into tickets, this isn't the fit.
Benefits- Base salary: $185,000 to $230,000
- Equity: We want our product managers to benefit from significant company growth, so equity is a meaningful part of how we structure PM compensation.
- Healthcare: Medical, dental, and vision
- Fully remote (US): Deep thinking time and partnership with peers in engineering, design, data, marketing, and ops matter more than a desk.
- Flexible PTO: We focus on results. Take what you need.
