Staff Product Engineer (São Paulo)

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 Engineering at LawnStarter

We build in small, focused initiative teams: a Product Engineer working alongside a PM and a designer, supported by an Engineering Manager who helps you grow. You'll also work shoulder-to-shoulder with engineering peers across initiatives in a shared codebase. The whole team owns whether the work moves its metric.

AI coding agents are a force multiplier here — they give a small, senior team the leverage to ship more, faster, and at a higher bar for quality. We hire engineers who are wired for ownership and energized by shipping to a real marketplace with customers and pros on both sides.

The Role

You're the engineering anchor of an initiative — working as part of a tight team with your PM and designer, and alongside engineering peers on adjacent initiatives. You have a hand in the full lifecycle: shaping the problem, deciding the technical approach, directing AI agents to implement much of the code, shipping to production, and — with your team — owning the outcome.

You're measured by impact, not by lines of code merged. When an agent can ship something safely, your job is to make sure it's done right and the metric moves. When the work calls for careful, hand-written code in a sensitive area, you write it yourself.

What makes this role exciting:

• End-to-End Ownership: From problem-framing through production to post-launch metric review, you see the whole arc and own the result with your team.
• True Product Partnership: Sit at the table with PM and design, bringing engineering judgment to product calls and product sense to engineering calls.
• Autonomy with Checkpoints: Make most technical calls yourself, with architect review on significant decisions and fast input from peers.
• Staff-Level Operation: Trusted to make the call, ship the hard thing, and stand behind the outcome.

What You'll Own

• Technical Approach: Architecture, data model, integration choices, rollout plan, observability, and rollback strategy for your initiative.
• Implementation Quality: Prompts, guardrails, evals, tests, and review loops to ensure agent-authored code is safe, correct, and production-ready.
• Cross-functional Partnership: Daily collaboration with PM and designer, regular interaction with engineering peers, and weekly check-ins with your EM.
• Initiative Outcome: The key metric the initiative is designed to move. Present results 2–4 weeks post-launch.
• High Shipping Bar: Ensure production correctness, security, performance, observability, and positive customer/pro experience.

Problems to Solve

• Leading AI Agents at Staff-Level Quality: Develop workflows that allow AI agents to ship production-ready code with senior engineer quality, using effective prompts, evaluations, tests, and review loops.
• Owning Decisions with High Autonomy: Move fast, maintain team alignment, and ensure accountability for technical decisions with architect review for major architectural choices and peer feedback.
• Shipping Outcomes, Not Features: Scope initiatives to impact key metrics, make disciplined build/no-build decisions, and follow up with post-launch analysis.

What Success Looks Like (Year 1)

• Initiative Outcomes Hit: Successfully shipped 3–4 initiatives, with at least two demonstrably moving their target metric.
• Reusable Agent Workflows: Developed prompts, evaluations, and review loops that are adopted by peers on other initiatives.
• Faster Cycle Time: Significantly reduced the median time from problem-framing to first production rollout.
• Quality Holds: No customer- or pro-facing regressions attributable to agent-authored code that bypassed review.
• Visible Leverage: Created and shared artifacts (runbooks, evals, agent workflows, post-launch reviews) that serve as valuable references for peers.

Requirements

Who You Are

• AI-Native: Proficient in using AI coding agents (e.g., Claude Code, Cursor, Codex) daily for production work, with strong opinions on prompts, evals, and agent workflows.
• Lead-Level Operator: Proven experience making critical technical calls, shipping complex features, and owning the outcomes.
• Outcome-Driven: Focused on driving metrics and improving user experience, comfortable analyzing post-launch data.
• Strong Horizontal Partner: Effective collaborator with PMs and designers, bringing engineering judgment to product decisions and vice-versa.
• Decisive and Documented: Capable of making and documenting architecture, data model, and rollout decisions quickly, seeking and incorporating fast input.
• Force Multiplier: Creates reusable assets and workflows that amplify impact beyond individual contributions.
• Customer- and Pro-Minded: Genuinely cares about the positive outcomes for both customers and service professionals in the marketplace.

Good to Know

• Individual Contributor Role: Focus on technical contribution with opportunities for growth, including a potential path to management.
• End-to-End Product Engineering: Ship features that move metrics; platform and architecture work are integrated into initiatives as needed.
• Hands-On with High Quality: Leverage AI for implementation while providing the critical judgment, design, safety, and accountability.
• Live Marketplace Shipping: Contribute to a platform with over $100M in annual bookings, impacting users weekly.

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 (customer & pro apps, web and mobile)
• Data: Redshift, dbt, Segment, Airflow
• Infra: AWS, Datadog, Sentry, GitHub Actions
• Documentation & Process: Brain (Claude Code skills + docs repo), Confluence, Jira

You don't need every box checked. You need deep skill in at least one of our stacks plus credible production experience with AI coding agents.