Staff Software Engineer, Product (Porto Alegre)

Staff Software Engineer, Product (Remote - Porto Alegre, 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 three brands on a single shared platform.

This is a remote role for candidates located in Porto Alegre, Brazil.

About Engineering at LawnStarter

We operate in small, focused initiative teams, where Product Engineers work closely with Product Managers and Designers. You will be supported by an Engineering Manager dedicated to your growth. Collaboration with engineering peers across initiatives within a shared codebase is key. The entire team shares ownership of the success of their work.

AI coding agents are a significant force multiplier, enabling our small, senior team to deliver more, faster, and with a higher standard of 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 of an initiative, you will be part of a close-knit team, collaborating with your PM and designer, and working alongside engineering peers on adjacent initiatives. You will be involved in the full lifecycle: shaping the problem, defining the technical approach, directing AI agents for 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 functionality, your role is to ensure it's done correctly and that the target metric improves. 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 framing 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 collaborate directly with Product and Design, contributing engineering judgment to product decisions and product sense to engineering decisions.
• Autonomy with Checkpoints: You will make most technical decisions independently, with architect review for significant architectural changes and rapid input from peers.
• Staff-Level Impact: You are trusted to make critical decisions, ship complex features, and stand behind the outcomes.

What You'll Own

• Technical Approach: Define the architecture, data model, integration choices, rollout plan, observability, and rollback strategy for your initiative. You will make most decisions independently, seeking architect review for major architectural changes, documenting them, and revisiting as needed based on data.
• 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 hand-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: Be accountable for the key metric your initiative is designed to move. You will present results with your PM 2-4 weeks post-launch.
• High Shipping Bar: Maintain a high standard for production correctness, security, performance, observability, and the overall experience for customers and service providers.

Problems to Solve

• Leading AI Agents at Staff-Level Quality: Develop workflows and processes that enable AI agents to produce production-ready code equivalent to that of a senior engineer, focusing on prompts, evaluations, tests, and observability.
• Owning Decisions with High Autonomy: Make and document technical decisions rapidly, leveraging architect review for significant architectural choices and peer feedback to refine your thinking, while maintaining team alignment and accountability.
• Shipping Outcomes, Not Just Features: Focus on initiatives measured by specific metrics (e.g., conversion rates, retention), scope work effectively to move these metrics, and maintain the discipline to follow up on post-launch results.

What Success Looks Like (Year 1)

• Successfully ship 3-4 initiatives end-to-end, with at least two demonstrably moving their target metrics.
• Develop AI agent workflows (prompts, evaluations, review loops) that are adopted by peers on other initiatives.
• Significantly reduce the median cycle time from problem framing to initial production rollout.
• Maintain high code quality, with no customer- or provider-facing regressions attributable to AI-authored code that bypassed your review.
• Create visible, reusable artifacts (e.g., runbooks, evaluations, 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