Staff Software Engineer, Product

About LawnStarter

LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, boasting over $100M in annual bookings. We are expanding our reach beyond lawn care to become a comprehensive provider for all home services, operating three distinct brands—LawnStarter, Lawn Love, and Home Gnome—on a unified, shared platform.

About Engineering at LawnStarter

Our engineering teams are structured into small, focused initiative units. As a Product Engineer, you will collaborate closely with a Product Manager and a designer, supported by an Engineering Manager dedicated to your professional growth. You will also work alongside engineering peers on various initiatives within a shared codebase. Team ownership is central to our approach, with collective accountability for achieving key metrics.

We leverage AI coding agents as a significant force multiplier, empowering our senior engineering team to deliver high-quality solutions more rapidly and efficiently. We seek engineers who demonstrate strong ownership and are motivated by deploying solutions to a dynamic marketplace serving both customers and service professionals.

The Role

As a Staff Software Engineer, Product, you will serve as the engineering anchor for a specific initiative, collaborating closely with your Product Manager and designer, and engaging with engineering peers on related projects. Your involvement spans the entire product lifecycle, from problem definition and technical approach decisions to directing AI agents for code implementation, deploying to production, and collectively owning the project's outcome.

Success in this role is measured by impact, not by lines of code. You will ensure that agent-generated code is correct and drives metric improvement. For sensitive areas requiring meticulous attention, you will personally write the code.

What makes this role exciting:

• End-to-End Shipping: You will manage the entire product lifecycle, from initial problem framing to production deployment and post-launch metric analysis, owning the results with your team.
• True Product Partnership: Collaborate directly with Product Managers and designers, contributing engineering expertise to product decisions and product insight to technical discussions.
• High Autonomy: Exercise significant technical decision-making, with architect review for major architectural choices and rapid peer feedback.
• Staff-Level Impact: Operate at a senior level, trusted to make critical decisions, deliver complex solutions, and be accountable for outcomes.

What You'll Own

• Technical Approach: Define the architecture, data model, integration strategies, rollout plans, observability, and rollback strategies for your initiatives. You will make most technical decisions, escalating significant architectural choices for architect review, documenting them, and iterating based on data.
• Implementation Quality: Ensure the quality of agent-authored code through effective prompts, guardrails, evaluations, tests, and review processes, guaranteeing safe, correct, and production-ready solutions. You are accountable for all code, including agent-generated, within our shared codebase.
• Cross-Functional Partnership: Maintain daily collaboration with your Product Manager on scope and tradeoffs, and with your designer on UX decisions and prototyping. Engage regularly with engineering peers and participate in weekly check-ins with your Engineering Manager.
• Initiative Outcome: Drive and own the key metrics for your initiatives. In partnership with your Product Manager, you will present post-launch results (2–4 weeks) and assess the success of the initiative.
• High Shipping Standards: Uphold rigorous standards for production correctness, security, performance, observability, and overall user experience for both customers and service professionals. While AI agents enhance speed, they do not compromise quality.

Problems to Solve

• Leading AI Agents at Staff-Level Quality: Develop and refine workflows for AI agents to produce code that meets senior engineering standards. This involves crafting effective prompts, implementing robust evaluations, writing comprehensive tests, and establishing observability to proactively identify regressions. The goal is to enable a small team to achieve disproportionately high output.
• Owning Decisions with High Autonomy: Leverage significant autonomy to make and document technical decisions rapidly. This includes seeking architect review for major architectural choices and engaging peers for critical feedback, all while maintaining speed, team alignment, and accountability for results.
• Shipping Outcomes, Not Just Features: Focus on delivering measurable outcomes, such as improved conversion rates, retention, or unit economics. You will be accountable for these metrics with your team, requiring strategic scoping, effective prioritization of what not to build, and diligent post-launch follow-up.

What Success Looks Like (Year 1)

• Achieved Initiative Outcomes: Successfully ship 3–4 end-to-end initiatives, with at least two demonstrating clear metric movement, validated by post-launch reviews.
• Scalable Agent Workflow: Develop and implement AI agent prompts, evaluations, and review processes that are adopted and utilized by peers across other initiatives.
• Accelerated Cycle Time: Significantly reduce the median time from problem framing to initial production rollout for your initiatives.
• Maintained Quality: Ensure no customer- or professional-facing regressions are attributable to agent-authored code that passed through your review.
• Visible Impact: Create reusable artifacts, such as runbooks, evaluations, AI agent workflows, and post-launch write-ups, that serve as valuable references for your peers.

Requirements

Who You Are

• AI-Native: Proficient in using AI coding agents like Claude Code, Cursor, or Codex daily for production work. You possess strong opinions on prompts, evaluations, agent loops, and review workflows, understanding when to leverage AI versus manual coding.
• Lead-Level Operator: Regardless of your current title, you have a proven track record of making critical decisions, delivering complex solutions, and taking accountability for their success.
• Outcome-Driven: You prioritize measurable impact, focusing on metric movement and user experience improvements, and actively analyze post-launch data to own the results.
• Strong Horizontal Partner: You effectively collaborate with Product Managers and designers, and work seamlessly with engineering peers in a shared codebase, contributing both engineering and product judgment to discussions.
• Decisive and Documented: You make well-reasoned architectural, data model, and rollout decisions, document them clearly, seek rapid input, and drive forward.
• Force Multiplier: Your contributions extend beyond individual initiatives through the creation of reusable artifacts such as AI agent workflows, evaluations, runbooks, and post-launch reviews.
• Customer and Pro-Minded: You are deeply committed to delivering positive outcomes for both customers and service professionals within a dynamic marketplace environment.

Good to Know

• Individual Contributor Role with Growth Potential: This is an individual contributor position, with people management responsibilities handled by the Engineering Manager. A path to management is available for those interested.
• End-to-End Product Engineering: Focus on shipping features that directly impact key metrics. Platform and architectural work are integrated within initiatives as needed to achieve desired outcomes.
• Hands-On with High Quality Standards: While AI agents manage much of the implementation, your role involves applying critical judgment, design principles, ensuring safety, and maintaining accountability for high-quality deliverables.
• Live Marketplace Impact: Your work will directly affect a live marketplace with over $100M in bookings, with customers and service professionals utilizing your deployments within the same week.

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 and professional applications across web and mobile platforms)
• Data: Redshift, dbt, Segment, Airflow
• Infrastructure: AWS, Datadog, Sentry, GitHub Actions
• Documentation & Process: Brain (Claude Code skills + docs repo), Confluence, Jira

While not every technology listed is a strict requirement, candidates should possess deep expertise in at least one of our core stacks, coupled with credible production experience utilizing AI coding agents.

Benefits

• Competitive annual base salary of USD $80,000–$100,000
• Flexible work environment: Work from anywhere
• High degree of ownership and autonomy
• Join a fast-moving team dedicated to building, learning, and professional growth