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Salary: USD 80,000 - 100,000 / annual
LawnStarter is the nation's leading on-demand marketplace for lawn care and related services, with over $150M in annual bookings, expanding into a one-stop shop for all home services.
You'll be LawnStarter's first Principal Quality Engineer, reporting directly to the Head of Engineering. The company has already built shared quality standards, working CI/CD gates, and AI tooling, but lacks dedicated leadership to own and evolve that vision. Currently, every QA engineer is heads-down on their own team with no bandwidth to unify standards, spread best practices, or drive the discipline forward.
This is not a traditional QA management role on day one. You won't approve tickets or chase bug counts. Instead, you'll take ownership of existing standards and tooling, work collaboratively with the QA squad to improve them, and push the state of quality engineering forward as the organization grows. As the QA squad scales, this role could evolve into direct people management.
You'll own the company-wide quality engineering roadmap and accountability framework defining what engineers, EMs, and PMs own at each stage. You'll design test strategy across the full stack (unit, component, contract, API, E2E, mobile, performance, accessibility), agreed with each team as their quality contract. You'll evolve AI-native quality tooling—AI agents and skills including Claude Code–style tools that any engineer can run on demand for test generation, code review, and quality guidance. You'll manage CI/CD and test infrastructure: required checks, quality gates, E2E and visual regression pipelines, performance budgets, mobile test automation across emulators and real device clouds, and deciding what blocks deploys versus what runs async. You'll tie production monitoring into incident response and build dashboards teams actually use. You'll provide technical mentorship of the QA discipline org-wide, mentoring QA engineers across squads and feeding input to their EMs for performance reviews.
Year 1 success means: a clear, communicated quality vision every product team understands; measurable improvement on existing gates (flakiness, pipeline cost, sync vs. async decisions); at least one new AI-native capability shipped that engineers use weekly; and a QA squad that feels led with concrete improvements to their work, tools, and standards.
You'll work with a team that already has solid foundations—this is continuous R&D and evolution, not a rewrite from scratch. The role requires listening to QAs who live in this daily, understanding pain points, and leading them toward what's next.
REQUIREMENTS:
- AI-native quality work experience: you already use AI to generate tests, not just autocomplete code. You've set up agentic tooling like Claude Code or MCP-based workflows so engineers can run on-demand test generation or code review, and you experiment with what AI can take off a team's plate next.
- Strategic thinking, not tool zealotry: you design testing approaches that fit a team's current maturity level, not mandate frameworks or coverage numbers before understanding context.
- Deeply hands-on across the test pyramid: you've built and maintained component, contract, API, E2E, and performance test suites yourself, not just reviewed them. You step in when engineering is blocked by pipeline issues.
- Patient teacher who ships: you coach engineers on testing practice and run enablement, but also personally build CI pipelines and tooling. You don't write docs and hope others implement them.
- Comfortable with influence without headcount, at least initially: you mentor QA engineers across squads and feed input to their EMs, but won't manage them day one. This works if you're motivated by discipline-wide technical influence. Prior experience hiring, coaching, and managing QA or engineering teams is a genuine plus, as this role could grow into direct QA squad management.
