Staff Software Engineer, Product (São Paulo)

Staff Software Engineer, Product (São Paulo) — Build the initiative that moves the metric

LawnStarter is hiring a Staff Software Engineer to serve as the engineering anchor for a product initiative in our shared codebase. This is a remote role for candidates located in São Paulo, Brazil—and it’s for engineers who don’t just ship code, but ship outcomes. With AI coding agents acting as a force multiplier, your small, senior team will move faster and at a higher quality bar—because you’ll set the bar, not just meet it.

If you’re the kind of engineer who can frame the problem, design the approach, direct AI safely, and then stand behind what reaches production—this is your place.

About LawnStarter

LawnStarter is the nation’s leading on-demand marketplace for lawn care and outdoor services, with $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, and Home Gnome—on a single shared platform.

About Engineering at LawnStarter

We build in small, focused initiative teams:

• Product Engineer working alongside a PM and designer
• Supported by an Engineering Manager who helps you grow
• Collaboration with engineering peers across adjacent initiatives in a shared codebase

Teams own whether the work moves the metric—not just whether it gets merged.

AI coding agents are a force multiplier for us: they help small, senior teams ship more, faster, and with strong quality. We hire engineers who are wired for ownership and energized by building for a real marketplace—customers and pros both benefit from what you ship.

About The Role

You’ll be the engineering anchor for an initiative—part of a tight loop with your PM and designer, and supported by engineering peers across adjacent initiatives. Your scope covers the full lifecycle:

• Shape the problem and define what “good” looks like
• Decide the technical approach (and document it)
• Direct AI agents to implement much of the code
• Ship to production
• Own the outcome with your team by reviewing results after launch

You’re measured by impact, not lines of code. When AI can safely ship, you ensure it ships correctly. When the problem calls for careful, hand-written code in sensitive areas, you write it yourself.

What You’ll Do

• Ship end-to-end initiatives—from problem-framing to production rollout to post-launch metric review
• Partner closely with PM and design:
  • Bring engineering judgment into product tradeoffs
  • Bring product sense into engineering decisions
  • Collaborate on UX decisions and in-tool prototyping
• Operate with autonomy—make most technical calls yourself, with:
  • Architect review on significant architectural decisions
  • Fast input from peers to pressure-test and de-risk
• Maintain a staff-level quality bar across production correctness, security, performance, observability, and end-user experience
• Build workflows that scale—your agent workflow and artifacts should be reusable across initiatives

What You’ll Own

• The technical approach for your initiative, including:
  • Architecture
  • Data model
  • Integration choices
  • Rollout plan
  • Observability
  • Rollback strategy
• Implementation quality that enables safe agent shipping:
  • Prompts and guardrails
  • Evals and review loop
  • Tests (including edge cases)
  • Code review discipline that matches the rest of the team’s standards
• Cross-functional partnership:
  • Daily working contact with your PM (scope, tradeoffs)
  • Regular collaboration with your designer (UX decisions, prototyping)
  • Weekly check-ins with your Engineering Manager
• The initiative outcome—the specific metric your initiative is set up to move:
  • With your PM, present results 2–4 weeks post-launch
  • Own the “did it work?” answer using real data
• A high bar for what ships:
  • Production correctness
  • Security and reliability
  • Performance and monitoring
  • Great experiences for both customers and pros

Problems to Solve

• Lead AI agents at a staff-level quality bar
  Most of the code on your initiative will be agent-authored. Your craft is ensuring it ships like a senior engineer wrote it:
  • Prompts that encode our conventions
  • Evals that catch issues before merge
  • Tests that cover edges
  • Observability that detects regressions before customers notice

  How do you build a workflow that lets a small team ship far more than its size would suggest?

• Own decisions with high autonomy
  You’ll have real latitude to make and document technical calls quickly—architect review for big architectural decisions, and peer input to validate your approach.

  How do you move fast, keep alignment, and stay accountable to the outcome?

• Ship outcomes, not features
  Each initiative is measured by a metric (e.g., conversion rate, retention curve, pro-funnel KPI, unit-economics shift).

  How do you scope what truly moves the number, decide what not to build, and follow up 2–4 weeks after launch?

What Success Looks Like (Year 1)

• Initiative outcomes hit:
  • Ship 3–4 initiatives end-to-end
  • At least two clearly move their metric (with proof via post-launch review)
• Agent workflow that travels:
  • Your prompts, evals, and review loop become reusable by peers on other initiatives
• Faster cycle time:
  • Meaningfully shorten median time from problem-framing to first production rollout
• Quality holds:
  • No customer- or pro-facing regressions traceable to agent-authored code that slipped through review
• Visible leverage:
  • Peers reference your artifacts—runbooks, evals, agent workflows, and post-launch write-ups

What We’re Looking For

Who you are:

• AI-native: You ship daily with tools like Claude Code, Cursor, Codex, or equivalent. You have real opinions about:
  • Prompts
  • Evals
  • Agent loops
  • Review workflows

  You also know when to let agents run and when to write it yourself.

• Operating at a lead level: No matter your current title, you’ve been the person making the call, shipping the hard thing, and standing behind whether it worked.
• Outcome-driven: You measure your week by:
  • “Did the metric move?”
  • “Did the experience get better?”

  You read post-launch dashboards and own the answer.

• A strong horizontal partner: You collaborate well with PMs, designers, and engineering peers in a shared codebase. You bring engineering judgment to product calls and product judgment to engineering calls.
• Decisive and documented: You make architecture, data-model, and rollout calls quickly—write them down, get fast input, and keep momentum.
• A force multiplier: Your impact compounds beyond your own initiative through reusable artifacts:
  • Agent workflows
  • Evals
  • Runbooks
  • Post-launch reviews
• Customer- and pro-minded: You understand this is a marketplace with real people on both sides, and you care about outcomes for both.

Good to Know

• Individual-contributor role with room to grow. People management sits with the EM, but management is an open door for those who want it.
• Product engineering, end-to-end: You ship features that move metrics—platform and architecture work happens within the initiative when the outcome demands it.
• Hands-on with a high quality bar: Agents handle much of the implementation; you bring the judgment, safety, and accountability.
• Live marketplace impact: With $100M+ in bookings, customers and pros use what you ship 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 (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 every box checked. You do need deep skill in at least one of our stacks plus credible production experience with AI coding agents.

Benefits

• Competitive compensation: USD $80,000–$100,000 annual base
• Work from anywhere
• High ownership and autonomy
• Fast-moving team that loves to build, learn, and grow

<p