Staff Software Engineer, Product

About LawnStarter

LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, boasting over $150M in annual bookings. We are expanding our reach beyond lawn care to become the premier one-stop shop for all home services, operating across three distinct brands: LawnStarter, Lawn Love, and Home Gnome, all powered by a single, shared platform.

About Engineering at LawnStarter

Our engineering team operates in small, focused initiative teams. A Product Engineer collaborates closely with a Product Manager (PM) and a designer, supported by an Engineering Manager dedicated to professional growth. You will also work alongside engineering peers across various initiatives within a shared codebase. The entire team shares ownership of achieving key metrics.

AI coding agents serve as a significant force multiplier, empowering our small, senior team to deliver more, faster, and with a higher standard of quality. We seek engineers who demonstrate strong ownership and are driven by shipping impactful solutions to a real marketplace serving both customers and service professionals.

The Role: Staff Software Engineer, Product

As a Staff Software Engineer, Product, you will be the engineering anchor for an initiative, working within a cohesive team alongside your PM and designer, and collaborating with engineering peers on related initiatives. Your involvement spans the full product lifecycle: from shaping the problem and defining the technical approach to directing AI agents for code implementation, deploying to production, and ultimately, owning the outcome with your team.

Your performance is measured by impact, not by lines of code. When an AI agent can safely deliver a solution, your responsibility is to ensure its correctness and that it contributes to moving the target metric. For sensitive areas requiring meticulous, hand-written code, you will personally develop it.

What Makes This Staff Software Engineer Role Exciting:

• End-to-End Ownership: You will manage the entire product arc, from initial problem framing through production deployment to post-launch metric review, owning the results with your team.
• True Product Partnership: You will actively participate in product and design discussions, contributing engineering judgment to product decisions and product sense to engineering strategies.
• High Autonomy: You will make most technical decisions independently, with architectural reviews for significant architectural choices and rapid input from peers.
• Staff-Level Impact: You are entrusted to make critical decisions, deliver complex solutions, and take accountability for the outcomes.

What You'll Own as a Staff Software Engineer:

• Technical Approach: Define the architecture, data model, integration choices, rollout plan, observability strategy, and rollback plan for your initiative. You will make most decisions, bringing significant architectural choices for architect review, documenting them, and iterating based on data.
• Implementation Quality: Ensure the prompts, guardrails, evaluations, tests, and review processes enable AI agents to produce safe, correct, and production-ready code. While most code will be agent-authored, you are accountable for its quality, held to the same high standard as the rest of the team in a shared codebase.
• Cross-Functional Partnership: Engage in daily collaboration with your Product Manager (scope, tradeoffs) and designer (UX decisions, in-tool prototyping), regular interaction with engineering peers, and weekly check-ins with your Engineering Manager.
• Initiative Outcome: Drive the specific metric the initiative aims to improve. Alongside your PM, you will present results 2–4 weeks post-launch, confirming the initiative's success.
• High Quality Bar: Maintain stringent standards for production correctness, security, performance, observability, and the overall experience for both customers and service professionals. AI agents enhance your speed without compromising quality.

Key Problems to Solve:

• Leading AI Agents at a Staff-Level Quality Bar: A significant portion of your initiative's code will be AI-authored. The craft is making them ship with the quality of a senior engineer's work, through effective prompts, robust evaluations, comprehensive tests, and proactive observability. Develop workflows that enable a small team to achieve disproportionately high output.
• Owning Decisions with High Autonomy: Exercise considerable latitude in making and documenting technical decisions swiftly, seeking architect review for major architectural choices and peer feedback for pressure-testing ideas. Balance speed, team alignment, and accountability for outcomes.
• Shipping Outcomes, Not Just Features: Each initiative is measured by a specific metric (e.g., conversion rate, retention, pro-funnel KPI, unit-economics shift). You are accountable for this metric alongside your team. Strategically scope projects, prioritize what not to build, and diligently follow up 2–4 weeks after launch to assess impact.

What Success Looks Like in Year 1:

• Achieved Initiative Outcomes: Successfully shipped 3–4 end-to-end initiatives, with at least two demonstrably moving their target metrics, validated by post-launch reviews.
• Scalable AI Agent Workflow: Developed prompts, evaluations, and review processes for AI agents that are adopted and utilized by peers across other initiatives.
• Faster Development Cycle Time: Significantly reduced the median time from problem framing to the initial production rollout for your initiatives.
• Maintained Quality: No customer- or pro-facing regressions attributable to agent-authored code that bypassed your review process.
• Visible Engineering Leverage: Created reusable artifacts (e.g., runbooks, evaluations, agent workflows, post-launch write-ups) that serve as valuable references for peers.

Requirements

Who You Are:

• AI-Native Engineer: You routinely use AI coding tools like Claude Code, Cursor, or Codex for daily production work. You possess strong opinions on prompts, evaluations, agent loops, and review workflows, and you instinctively know when to leverage AI versus writing code manually.
• Lead-Level Operator: Regardless of your current title, you have a proven track record of making critical decisions, delivering challenging projects, and taking full accountability for their success.
• Outcome-Driven: Your focus is on measurable impact, evaluating your work by whether metrics improved and user experience enhanced. You actively analyze post-launch dashboards and own the results.
• Strong Cross-Functional Partner: You effectively collaborate with Product Managers and designers, and work seamlessly with engineering peers in a shared codebase. You bring valuable engineering judgment to product discussions and product insight to engineering decisions.
• Decisive and Documented: You make well-considered architecture, data-model, and rollout decisions, document them clearly, seek rapid input, and drive forward.
• Force Multiplier: Your contributions extend beyond your immediate initiative, creating reusable artifacts such as agent workflows, evaluations, runbooks, and post-launch reviews that amplify team impact.
• Customer and Pro-Minded: You are deeply invested in the outcomes for both customers and service professionals within our dynamic marketplace.

Good to Know:

• Individual Contributor Role with Growth Path: This is an individual contributor position, with people management responsibilities residing with the Engineering Manager. However, a path into management is available for those interested.
• End-to-End Product Engineering: You will ship features directly impacting metrics. Platform and architectural work are integrated into initiatives as needed to achieve outcomes.
• Hands-On with High Quality Bar: While AI agents handle much of the implementation, your role involves critical judgment, design oversight, ensuring safety, and accountability for high-quality delivery.
• Shipping to a Live Marketplace: With over $150M in bookings, your work will be used by real customers and service professionals within weeks of deployment.

Tech You'll Touch:

• AI Agents: Claude Code, Cursor, Codex, internal agent stack, MCP servers, evals tooling
• Backend: PHP/Laravel
• Frontend: TypeScript/React/React Native (for customer & pro apps, web and mobile)
• Data: Redshift, dbt, Segment, Airflow
• Infrastructure: AWS, Datadog, Sentry, GitHub Actions
• Documentation & Process: Brain (Claude Code skills + docs repo), Confluence, Jira

You don't need to check every box. We require deep skill in at least one of our core stacks combined with credible production experience utilizing AI coding agents.

Benefits:

• Competitive salary of USD $85,000–$125,000 annual base
• Work from anywhere (remote flexibility)
• High ownership and autonomy in your role
• Fast-moving team dedicated to building, learning, and growing