About LawnStarter
LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $100M in annual bookings. We operate across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform, and we've been profitable for two years running. We're expanding beyond lawn care to become the one-stop shop for all home services.
About Product at LawnStarter
Home services is a massive, broken market. For homeowners, getting reliable, fairly priced service is a hassle of phone tag, no-shows, and surprise quotes. For the Pros who do the work, running a business means chasing customers, dead time between jobs, and unpaid admin. LawnStarter is the marketplace that fixes both sides.
We proved the model with lawn care it works at scale, profitably, across millions of jobs. In the last year we extended it to a second service: pool cleaning, now live in select markets. Getting there meant building the first version of a product that can onboard customers and Pros, match the two sides, get the job done, and handle the exceptions when it doesn't go to plan.
The Role
This is LawnStarter's first Director of Product Management the leader between the VP of Product and a team of three PMs (and the hires that follow).
The mandate is simple to state and hard to do: ship value across growth, retention, and profitability by building a great product for customers and Pros. Concretely, that means taking us from one profitable-at-scale vertical to two, setting the path from two to n, while still aggressively improving our core lawn service.
What Makes This Role Different
You build the layer, not inherit it. This is a brand-new layer between the VP and the PMs. You define how the team works, the bar for the craft, and the operating model you're not slotting into someone else's machine.It's a marketplace, so the obvious answer is usually wrong. Change a price and you move conversion, Pro claim rates, margin, and retention all at once. Almost every decision has second-order effects across customers, Pros, and the business. You think in systems, not features.You multiply a strong team this isn't a turnaround. The PMs are already good. The job is to get extraordinary outcomes from extraordinary people while still doing the hardest work yourself. Player-coach, not figurehead.Strategic bets and patient optimization, both. You'll open new verticals and compound a few points of conversion at a time and know which the moment calls for.What You'll Own
The PM team: Lead, coach, and multiply three already-strong PMs and hire more as we grow.Prioritization: Own the growth/retention/profitability tradeoffs on one shared roadmap what gets built, what waits, what we kill.Multi-service strategy: Turn one proven vertical into a repeatable playbook across services, designing for customers and Pros as one system.Agent-native direction: Own how AI and agents show up in what we build for our team, our customers, and our Pros.Cross-functional partnership: Be the product leader the rest of the company trusts to make the right calls.Problems to Solve
Abstracting one product into a multi-service platform. Every service has different economics, quality signals, and Pro workflows. How do we judge Pro quality when services are nothing alike? Price any service by location and job complexity? Guarantee quality on every job, not just lawns? You'll decide what generalizes and what stays service-specific, then sequence the build to a second profitable vertical a platform that absorbs that variation instead of forking under it.
Prioritizing across three goals with one capacity. Growth, retention, and profitability all want the roadmap, and engineering capacity is finite a win on one can cost you on another. You'll own the sequencing and tradeoffs, and say no clearly and often, with reasons people respect.
Building for the agent era. We believe products must now be built to use agents (to move faster and serve customers and Pros better) and to serve agents (so the platform works when the buyer or the worker is an AI). Almost no one has a playbook for this you'll help write ours.
What Success Looks Like (Year 1)
The team ships at a higher ceiling: The same strong PMs are visibly doing their best work better outcomes, sharper scoping, faster shipping.Wins in all three goals: Measurable progress on growth, retention, and profitability not one at the expense of the others.Second vertical on track: Pool cleaning progressing toward profitable-at-scale, with a repeatable playbook for the verticals after it taking shape.A stronger brand through quality: Measurable improvement in the quality of our core service, and a clear plan with the growth team to win AI-driven channels.An agent-native vision: A clear roadmap for winning in an agent-driven world, with the first bets already underway.Requirements
Who You Are
AI-native and agent-curious. You use AI every day and push the team to do the same. You believe agents are the next platform shift, and you're energized by the open question of what an agent-driven world means for LawnStarter a genuine thought partner on it, not someone who shows up with all the answers. This is unlikely to be a good fit if you treat AI as a productivity hack.
A player-coach who multiplies talent. You get extraordinary outcomes from already-strong people coaching, raising the bar, unblocking and you still do the hardest work yourself when it counts. You know the difference between leading and controlling. This is unlikely to be a good fit if you need to "fix" a broken team to feel useful, or if you've moved fully into management and don't want to touch the product directly.
A systems thinker. You see inputs, rules, feedback loops, and second-order effects, and you hold the customer side and the Pro side in your head as one connected machine. This is unlikely to be a good fit if you think in isolated features and miss how a change ripples through the rest of the system.
A brutal prioritizer. You say no well you sequence ruthlessly, kill good-but-not-now work, and protect the team's focus. This is unlikely to be a good fit if you avoid the hard conversations prioritization requires.
A great cross-functional partner. You earn the trust of designers, engineers, data, finance, and ops by speaking their language and making decisions they respect. This is unlikely to be a good fit if you treat other functions as service providers rather than partners.
Obsessive about scoping and user experience. You cut scope to the essential and sweat how the product actually feels to use. This is unlikely to be a good fit if you ship the first version that technically works without caring whether it's genuinely good.
This Role Is NOT
A pure people-management role. You lead a team and stay in the work the hardest problems are yours to help solve, not just to assign. If you don't want to touch a spec again, this isn't it.A solo-IC role. You lead and grow a team. If you want to own a domain alone with no reports, look at our Senior PM roles instead.A turnaround. The team is already strong. If you're energized by fixing broken teams, this won't scratch that itch.A fit for an AI skeptic. We believe the agent shift is real and urgent. If you're not convinced, you'll be fighting the company's direction.A role with a finished playbook. Multi-service and agent-native product are things we're figuring out as we go. If you need established processes and proven paths, this will be frustrating.Benefits
Equity: A significant leadership equity package. You'll have high impact on our growth, retention, and profitability. We want you invested in that outcome.Base salary: 200k - 250kHealthcare: Medical, dental, and vision.Fully remote: Work from anywhere in the US. Leading a distributed team and doing deep product work both require focus and trust we give you both.Flexible PTO: We focus on results. Take what you need.LawnStarter provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. We comply with applicable state and local laws governing nondiscrimination in employment.
Read Less About LawnStarter
LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $100M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform.
About Service Delivery at LawnStarter
We make a promise on both sides of the marketplace: customers get a job done well, and Pros get paid fairly for doing it. Service delivery is everything that happens after a customer books keeping that promise through completion, support, and the moments when things don't go to plan.
This is the hard part of running a marketplace: we broker work we can't directly see, between two parties whose interests sometimes collide. Get it right and people stay for years. Get it wrong and you lose customers, Pros, or both. Trust is the product and increasingly, the systems that protect it are AI-powered.
Requirements
The Role
This is a broad Senior PM role on the quality, trust, and communication side of service delivery setting the right expectations on both sides, steering Pros to deliver great work, resolving conflicting interests fairly, and making our AI-powered support genuinely good. You'll work on live, high-scale systems with a mandate to make them better.
Service delivery is a big area with more than one PM in it. You'll work alongside them; your center of gravity is the trust between both sides of the marketplace.
What makes this role different:
It's a real area of impact, not a single feature. You'll shape strategy, policy, and the systems behind a whole slice of the post-booking experience not optimize one screen.It's inherently two-sided. You work for customers and Pros at once, and you're often the one arbitrating between them. Pleasing one side at the other's expense is failure.AI is a core tool, not a side project. Support and outreach already run on AI. You'll push how far that goes and build the evals that prove it's good before we trust it with more.Problems to Solve
Getting expectations right before the work ever starts. Most service failures aren't bad work they're mismatched expectations. The grass grew a tier past what was booked; "deep clean" meant something different to each side; the yard didn't match the photos. You'll make sure what's promised to the Pro matches what the customer actually expects, that those expectations are the right ones for the property and service, and that Pros are steered toward delivering great work. Every mismatch you prevent up front is a conflict you never have to resolve later.
Arbitrating genuinely competing interests. A customer wants a date the Pro can't commit to. The grass is long enough to need a different price tier than booked. The job wasn't what the listing photos suggested. 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) decision systems that resolve these fairly and consistently at scale and make the judgment call yourself when there's no clean answer.
Making AI trustworthy enough to do more which means evals. Customer-side AI already handles ~34% of support at roughly a penny per message, and Pro-side support is still to be built. Expanding either is gated on one hard, ongoing, technical thing: can we prove the AI resolved a case rather than just closed it? You'll own the eval systems golden datasets, automated judges, regression detection, human-review sampling that define what "good" means for an open-ended conversation, gate every change, and catch quality drift before a customer feels it. This is the deep, unglamorous work that makes a slick demo safe to scale.
Messaging that connects both sides and quietly protects the marketplace. The inbox is how 500K+ customers and 20K+ Pros coordinate across all three brands and the record we lean on when something goes sideways. It also has to moderate: catching when a relationship is drifting off-platform (disintermediation) or a conversation is heating into conflict. You'll keep communication easy for the legitimate 99% while spotting the patterns that quietly cost us customers, Pros, and revenue.
What Success Looks Like (Year 1)
Expectations match on both sides: Pros know exactly what each job requires, customers get what they expected, and fewer jobs go sideways from misalignment in the first place.Competing interests resolve faster and more fairly: A clearer resolution model with measurable consistency and more of these conflicts prevented up front by better expectation-setting.AI is provably good, and does more: An eval suite gates AI changes so no quality regression ships unseen and on that foundation, higher resolution on customer support plus a first version of Pro-side AI support live.Messaging connects and protects: Measurable improvement in messaging reliability and engagement, plus working moderation that catches off-platform leakage and conflict early.Who You Are
AI-native. You use AI daily in your own work, and you have real intuition for how to measure whether an AI experience is actually good not just whether it shipped. You've built or owned evals, or you're hungry to, because you know that's what separates a trustworthy agent from a demo. This is unlikely to be a good fit if you treat LLM quality as a vibe check or as engineering's problem to figure out.
Comfortable making two-sided calls. You can hold both the customer's and the Pro's interest in your head at once, and you're willing to make the call when they conflict clearly, and with a rationale you'd defend to either side. This is unlikely to be a good fit if you're a people-pleaser who can't say no, or if you instinctively optimize for one side and forget the other exists.
You design for the right outcome up front. You're not satisfied grading work after the fact you'd rather get the expectations right at the start so the job goes well in the first place, for both the customer and the Pro. This is unlikely to be a good fit if you gravitate to measuring and auditing results over shaping them before they happen.
A marketplace systems thinker. You see service delivery as a system of incentives, policies, and feedback loops not a set of screens and you design rules that hold up across edge cases and bad actors. This is unlikely to be a good fit if your instinct is to solve every problem with UI rather than incentives and policy.
Data-informed. You live in the numbers that matter here CSAT, resolution rate, eval scores, churn, deflection and you know when the data is thin enough that a judgment call is needed. This is unlikely to be a good fit if you either ignore data or refuse to move without perfect information.
Technically fluent. You partner with engineers on how AI and messaging systems work and give real feedback on design tradeoffs. You don't write production code, but you don't treat the systems as a black box either. This is unlikely to be a good fit if you need everything translated out of technical terms first.
This Role Is NOT
A support PM role. Support is one surface of a much broader product area. If you picture your days as managing a ticket queue or a help center, this isn't that.The internal-AI role. We have a separate PM driving AI adoption in internal tooling. This role is about AI in the user-facing service-delivery experience customers and Pros, not internal teams.A greenfield 01 role. These systems are live and serving hundreds of thousands of people today. You'll improve and re-architect under real load, not build from a blank page.A single-audience role. You serve and arbitrate between both customers and Pros. If you only want to think about one side of the marketplace, the tension here will be uncomfortable.Benefits
Base salary: $140,000 - $170,000Equity: The systems you'll work on touch every customer and Pro quality, trust, and retention all run through service delivery. We want you invested in the long-term outcome.Healthcare: Medical, dental, and visionFully remote: Work from anywhere in the US. This role requires deep focus and close partnership with engineering and ops we trust you to manage your environment.Flexible PTO: We Focus On ResultsLawnStarter provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. We comply with applicable state and local laws governing nondiscrimination in employment.
Read LessAbout LawnStarter
LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $100M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform.
About Service Delivery at LawnStarter
We make a promise on both sides of the marketplace: customers get a job done well, and Pros get paid fairly for doing it. Service delivery is everything that happens after a customer books keeping that promise through completion, support, and the moments when things don't go to plan.
This is the hard part of running a marketplace: we broker work we can't directly see, between two parties whose interests sometimes collide. Get it right and people stay for years. Get it wrong and you lose customers, Pros, or both. Trust is the product and increasingly, the systems that protect it are AI-powered.
Requirements
The Role
This is a broad Senior PM role on the quality, trust, and communication side of service delivery setting the right expectations on both sides, steering Pros to deliver great work, resolving conflicting interests fairly, and making our AI-powered support genuinely good. You'll work on live, high-scale systems with a mandate to make them better.
Service delivery is a big area with more than one PM in it. You'll work alongside them; your center of gravity is the trust between both sides of the marketplace.
What makes this role different:
It's a real area of impact, not a single feature. You'll shape strategy, policy, and the systems behind a whole slice of the post-booking experience not optimize one screen.It's inherently two-sided. You work for customers and Pros at once, and you're often the one arbitrating between them. Pleasing one side at the other's expense is failure.AI is a core tool, not a side project. Support and outreach already run on AI. You'll push how far that goes and build the evals that prove it's good before we trust it with more.Problems to Solve
Getting expectations right before the work ever starts. Most service failures aren't bad work they're mismatched expectations. The grass grew a tier past what was booked; "deep clean" meant something different to each side; the yard didn't match the photos. You'll make sure what's promised to the Pro matches what the customer actually expects, that those expectations are the right ones for the property and service, and that Pros are steered toward delivering great work. Every mismatch you prevent up front is a conflict you never have to resolve later.
Arbitrating genuinely competing interests. A customer wants a date the Pro can't commit to. The grass is long enough to need a different price tier than booked. The job wasn't what the listing photos suggested. 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) decision systems that resolve these fairly and consistently at scale and make the judgment call yourself when there's no clean answer.
Making AI trustworthy enough to do more which means evals. Customer-side AI already handles ~34% of support at roughly a penny per message, and Pro-side support is still to be built. Expanding either is gated on one hard, ongoing, technical thing: can we prove the AI resolved a case rather than just closed it? You'll own the eval systems golden datasets, automated judges, regression detection, human-review sampling that define what "good" means for an open-ended conversation, gate every change, and catch quality drift before a customer feels it. This is the deep, unglamorous work that makes a slick demo safe to scale.
Messaging that connects both sides and quietly protects the marketplace. The inbox is how 500K+ customers and 20K+ Pros coordinate across all three brands and the record we lean on when something goes sideways. It also has to moderate: catching when a relationship is drifting off-platform (disintermediation) or a conversation is heating into conflict. You'll keep communication easy for the legitimate 99% while spotting the patterns that quietly cost us customers, Pros, and revenue.
What Success Looks Like (Year 1)
Expectations match on both sides: Pros know exactly what each job requires, customers get what they expected, and fewer jobs go sideways from misalignment in the first place.Competing interests resolve faster and more fairly: A clearer resolution model with measurable consistency and more of these conflicts prevented up front by better expectation-setting.AI is provably good, and does more: An eval suite gates AI changes so no quality regression ships unseen and on that foundation, higher resolution on customer support plus a first version of Pro-side AI support live.Messaging connects and protects: Measurable improvement in messaging reliability and engagement, plus working moderation that catches off-platform leakage and conflict early.Who You Are
AI-native. You use AI daily in your own work, and you have real intuition for how to measure whether an AI experience is actually good not just whether it shipped. You've built or owned evals, or you're hungry to, because you know that's what separates a trustworthy agent from a demo. This is unlikely to be a good fit if you treat LLM quality as a vibe check or as engineering's problem to figure out.
Comfortable making two-sided calls. You can hold both the customer's and the Pro's interest in your head at once, and you're willing to make the call when they conflict clearly, and with a rationale you'd defend to either side. This is unlikely to be a good fit if you're a people-pleaser who can't say no, or if you instinctively optimize for one side and forget the other exists.
You design for the right outcome up front. You're not satisfied grading work after the fact you'd rather get the expectations right at the start so the job goes well in the first place, for both the customer and the Pro. This is unlikely to be a good fit if you gravitate to measuring and auditing results over shaping them before they happen.
A marketplace systems thinker. You see service delivery as a system of incentives, policies, and feedback loops not a set of screens and you design rules that hold up across edge cases and bad actors. This is unlikely to be a good fit if your instinct is to solve every problem with UI rather than incentives and policy.
Data-informed. You live in the numbers that matter here CSAT, resolution rate, eval scores, churn, deflection and you know when the data is thin enough that a judgment call is needed. This is unlikely to be a good fit if you either ignore data or refuse to move without perfect information.
Technically fluent. You partner with engineers on how AI and messaging systems work and give real feedback on design tradeoffs. You don't write production code, but you don't treat the systems as a black box either. This is unlikely to be a good fit if you need everything translated out of technical terms first.
This Role Is NOT
A support PM role. Support is one surface of a much broader product area. If you picture your days as managing a ticket queue or a help center, this isn't that.The internal-AI role. We have a separate PM driving AI adoption in internal tooling. This role is about AI in the user-facing service-delivery experience customers and Pros, not internal teams.A greenfield 01 role. These systems are live and serving hundreds of thousands of people today. You'll improve and re-architect under real load, not build from a blank page.A single-audience role. You serve and arbitrate between both customers and Pros. If you only want to think about one side of the marketplace, the tension here will be uncomfortable.Benefits
Base salary: $140,000 - $170,000Equity: The systems you'll work on touch every customer and Pro quality, trust, and retention all run through service delivery. We want you invested in the long-term outcome.Healthcare: Medical, dental, and visionFully remote: Work from anywhere in the US. This role requires deep focus and close partnership with engineering and ops we trust you to manage your environment.Flexible PTO: We Focus On ResultsLawnStarter provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. We comply with applicable state and local laws governing nondiscrimination in employment.
Read LessAbout LawnStarter
LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $100M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform.
About Service Delivery at LawnStarter
We make a promise on both sides of the marketplace: customers get a job done well, and Pros get paid fairly for doing it. Service delivery is everything that happens after a customer books keeping that promise through completion, support, and the moments when things don't go to plan.
This is the hard part of running a marketplace: we broker work we can't directly see, between two parties whose interests sometimes collide. Get it right and people stay for years. Get it wrong and you lose customers, Pros, or both. Trust is the product and increasingly, the systems that protect it are AI-powered.
Requirements
The Role
This is a broad Senior PM role on the quality, trust, and communication side of service delivery setting the right expectations on both sides, steering Pros to deliver great work, resolving conflicting interests fairly, and making our AI-powered support genuinely good. You'll work on live, high-scale systems with a mandate to make them better.
Service delivery is a big area with more than one PM in it. You'll work alongside them; your center of gravity is the trust between both sides of the marketplace.
What makes this role different:
It's a real area of impact, not a single feature. You'll shape strategy, policy, and the systems behind a whole slice of the post-booking experience not optimize one screen.It's inherently two-sided. You work for customers and Pros at once, and you're often the one arbitrating between them. Pleasing one side at the other's expense is failure.AI is a core tool, not a side project. Support and outreach already run on AI. You'll push how far that goes and build the evals that prove it's good before we trust it with more.Problems to Solve
Getting expectations right before the work ever starts. Most service failures aren't bad work they're mismatched expectations. The grass grew a tier past what was booked; "deep clean" meant something different to each side; the yard didn't match the photos. You'll make sure what's promised to the Pro matches what the customer actually expects, that those expectations are the right ones for the property and service, and that Pros are steered toward delivering great work. Every mismatch you prevent up front is a conflict you never have to resolve later.
Arbitrating genuinely competing interests. A customer wants a date the Pro can't commit to. The grass is long enough to need a different price tier than booked. The job wasn't what the listing photos suggested. 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) decision systems that resolve these fairly and consistently at scale and make the judgment call yourself when there's no clean answer.
Making AI trustworthy enough to do more which means evals. Customer-side AI already handles ~34% of support at roughly a penny per message, and Pro-side support is still to be built. Expanding either is gated on one hard, ongoing, technical thing: can we prove the AI resolved a case rather than just closed it? You'll own the eval systems golden datasets, automated judges, regression detection, human-review sampling that define what "good" means for an open-ended conversation, gate every change, and catch quality drift before a customer feels it. This is the deep, unglamorous work that makes a slick demo safe to scale.
Messaging that connects both sides and quietly protects the marketplace. The inbox is how 500K+ customers and 20K+ Pros coordinate across all three brands and the record we lean on when something goes sideways. It also has to moderate: catching when a relationship is drifting off-platform (disintermediation) or a conversation is heating into conflict. You'll keep communication easy for the legitimate 99% while spotting the patterns that quietly cost us customers, Pros, and revenue.
What Success Looks Like (Year 1)
Expectations match on both sides: Pros know exactly what each job requires, customers get what they expected, and fewer jobs go sideways from misalignment in the first place.Competing interests resolve faster and more fairly: A clearer resolution model with measurable consistency and more of these conflicts prevented up front by better expectation-setting.AI is provably good, and does more: An eval suite gates AI changes so no quality regression ships unseen and on that foundation, higher resolution on customer support plus a first version of Pro-side AI support live.Messaging connects and protects: Measurable improvement in messaging reliability and engagement, plus working moderation that catches off-platform leakage and conflict early.Who You Are
AI-native. You use AI daily in your own work, and you have real intuition for how to measure whether an AI experience is actually good not just whether it shipped. You've built or owned evals, or you're hungry to, because you know that's what separates a trustworthy agent from a demo. This is unlikely to be a good fit if you treat LLM quality as a vibe check or as engineering's problem to figure out.
Comfortable making two-sided calls. You can hold both the customer's and the Pro's interest in your head at once, and you're willing to make the call when they conflict clearly, and with a rationale you'd defend to either side. This is unlikely to be a good fit if you're a people-pleaser who can't say no, or if you instinctively optimize for one side and forget the other exists.
You design for the right outcome up front. You're not satisfied grading work after the fact you'd rather get the expectations right at the start so the job goes well in the first place, for both the customer and the Pro. This is unlikely to be a good fit if you gravitate to measuring and auditing results over shaping them before they happen.
A marketplace systems thinker. You see service delivery as a system of incentives, policies, and feedback loops not a set of screens and you design rules that hold up across edge cases and bad actors. This is unlikely to be a good fit if your instinct is to solve every problem with UI rather than incentives and policy.
Data-informed. You live in the numbers that matter here CSAT, resolution rate, eval scores, churn, deflection and you know when the data is thin enough that a judgment call is needed. This is unlikely to be a good fit if you either ignore data or refuse to move without perfect information.
Technically fluent. You partner with engineers on how AI and messaging systems work and give real feedback on design tradeoffs. You don't write production code, but you don't treat the systems as a black box either. This is unlikely to be a good fit if you need everything translated out of technical terms first.
This Role Is NOT
A support PM role. Support is one surface of a much broader product area. If you picture your days as managing a ticket queue or a help center, this isn't that.The internal-AI role. We have a separate PM driving AI adoption in internal tooling. This role is about AI in the user-facing service-delivery experience customers and Pros, not internal teams.A greenfield 01 role. These systems are live and serving hundreds of thousands of people today. You'll improve and re-architect under real load, not build from a blank page.A single-audience role. You serve and arbitrate between both customers and Pros. If you only want to think about one side of the marketplace, the tension here will be uncomfortable.Benefits
Base salary: $140,000 - $170,000Equity: The systems you'll work on touch every customer and Pro quality, trust, and retention all run through service delivery. We want you invested in the long-term outcome.Healthcare: Medical, dental, and visionFully remote: Work from anywhere in the US. This role requires deep focus and close partnership with engineering and ops we trust you to manage your environment.Flexible PTO: We Focus On ResultsLawnStarter provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. We comply with applicable state and local laws governing nondiscrimination in employment.
Read Less