Jobs at LawnStarter

Own LawnStarter’s company-wide quality engineering vision, standards, test strategy, CI/CD gates, automation infrastructure, and production quality signals. Lead and mentor the QA discipline without initially managing direct reports, improve testing across the pyramid, advance AI-native quality tooling, and guide teams toward effective quality practices. The role is hands-on, involving test infrastructure, pipelines, performance and mobile testing, tooling development, technical mentorship, and continuous quality improvement.

Own the end-to-end Service Experience product strategy and roadmap for a two-sided home-services marketplace. Lead AI-powered customer and Pro support, evaluation systems, trust and conflict-resolution policies, and AI-driven experience innovation. Own Contribution LTV and brand-promise metrics, prototype with LLMs, analyze transcripts and data, and influence senior leaders and cross-functional peers without direct reports. Success includes scaling high-quality AI resolution, improving profitability and service outcomes, and delivering an AI experience proof of concept.

Lead distributed teams of 4–5 engineers, owning people development, delivery reliability, team health, cross-functional alignment, technical direction, and AI adoption. Build career growth plans, address performance and conflict directly, manage delivery risks, support architecture decisions, and improve measurable team throughput while maintaining software quality.

Owns product initiatives end to end, including problem framing, architecture, implementation quality, AI-agent workflows, production launches, observability, and post-launch metrics. Partners closely with product managers, designers, engineering peers, and engineering management. Makes autonomous technical decisions, ensures security and performance, and delivers measurable marketplace outcomes across a shared PHP/Laravel and TypeScript/React platform.

Owner of Growth experimentation and acquisition-to-conversion analytics: design rigorous tests (power, sample size, anytime-valid monitoring), produce readouts, and build a Python/dbt/Lightdash self-serve experimentation layer. Maintain a trusted funnel model (visitor→lead→customer) across channels, reduce reruns via instrumentation checks, and partner with CRO, Growth PMs, and performance marketing to turn analysis into measurable conversion wins.