Principal Product Manager

About Lawn Starter

Lawn Starter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $150M in bookings. We're expanding beyond lawn care to become the one-stop shop for home services: three brands (Lawn Starter, Lawn Love, Home Gnome), one shared platform.

Our BHAG: 1+ job per household, every year. Getting there means winning on four fronts at once: more customers, more Pros, excellent service experience for both sides, and an AI-run company that moves faster than its size should allow. We've organized around those bets as swim lanes:
New Customer Acquisition, Strengthen Supply, Service Experience, and AI & Operating Excellence.

This 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.

• 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.

• 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.

Making 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?

• 50%+ of support inquiries resolved by AI with high customer and Pro satisfaction, behind an eval suite blocking regressions, plus a first version of…