Staff Software Engineer, Product (Campinas)

Staff Software Engineer, Product (Remote - Campinas, Brazil)

LawnStarter is the leading on-demand marketplace for lawn care and outdoor services, with over $100 million in annual bookings. We are expanding to become the go-to platform for all home services, operating across multiple brands on a single, shared platform.

About Engineering at LawnStarter

We operate in small, focused initiative teams, where a Product Engineer collaborates closely with a Product Manager and a Designer. Supported by an Engineering Manager, you will also work alongside engineering peers across various initiatives within a shared codebase. The entire team shares ownership of the success metrics for their work.

AI coding agents are a significant advantage, empowering our small, senior team to deliver more, faster, and with higher quality. We seek engineers who are driven by ownership and energized by shipping products to a real marketplace with both customers and service providers.

The Role

As the engineering anchor for an initiative, you will be part of a close-knit team, working alongside your PM and designer, and collaborating with engineering peers on adjacent initiatives. You will be involved in the entire product lifecycle: shaping the problem, defining the technical approach, directing AI agents for code implementation, shipping to production, and owning the outcome with your team.

Your performance will be measured by impact, not lines of code. When an AI agent can safely ship a feature, your role is to ensure it's done correctly and that the key metrics improve. For sensitive areas requiring careful, hand-written code, you will be responsible for that implementation.

What Makes This Role Exciting:

• End-to-End Ownership: From problem definition through production and post-launch metric review, you will see the entire arc and own the results with your team.
• True Product Partnership: You will actively participate in product decisions alongside PM and Design, contributing engineering judgment to product discussions and product sense to engineering ones.
• Autonomy with Support: You will make most technical decisions independently, with architect review for significant architectural choices and rapid input from peers.
• Staff-Level Impact: You will be trusted to make critical decisions, ship complex features, and stand behind the outcomes.

What You'll Own

• Technical Approach: Define architecture, data models, integration strategies, rollout plans, observability, and rollback strategies for your initiative. You will make most decisions and bring significant architectural proposals for review, documenting them and revisiting as needed.
• Implementation Quality: Ensure the quality of AI-generated code through effective prompts, guardrails, evaluations, tests, and review processes. You are accountable for AI-authored code, held to the same high standards as manually written code.
• Cross-Functional Partnership: Engage daily with your PM on scope and tradeoffs, with your designer on UX and prototyping, collaborate regularly with engineering peers, and have weekly check-ins with your Engineering Manager.
• Initiative Outcome: Drive the key metric your initiative is designed to impact. You will present results with your PM 2-4 weeks post-launch, clearly articulating the success of the initiative.
• High Shipping Bar: Maintain a high standard for production correctness, security, performance, observability, and the overall experience for customers and service providers. AI agents are accelerators, not compromises on quality.

Problems to Solve

• Leading AI Agents at a Staff-Level Quality Bar: Develop workflows where AI agents produce code equivalent to that of a senior engineer, focusing on prompts, evaluations, and review processes to ensure safety and correctness.
• Owning Decisions with High Autonomy: Make and document technical decisions quickly, seeking architect review for major architectural choices and leveraging peer feedback to refine your thinking.
• Shipping Outcomes, Not Features: Focus on initiatives measured by specific metrics, scoping work effectively, prioritizing ruthlessly, and following up post-launch to demonstrate impact.

What Success Looks Like (Year 1)

• Successfully ship 3-4 initiatives end-to-end, with at least two demonstrably moving their key metrics.
• Develop and share AI agent workflows, prompts, and evaluation strategies that are adopted by other teams.
• Significantly reduce the median cycle time from problem framing to initial production rollout for your initiatives.
• Maintain high quality standards, with no customer- or provider-facing regressions attributable to agent-authored code slipping through your review.
• Become a visible force multiplier, with peers referencing your artifacts (runbooks, evaluations, post-launch reviews) as valuable resources.

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, evaluations, and review workflows. You know when to leverage AI and when to write code yourself.
• **Lead-