Staff Software Engineer, Product (Belo Horizonte)

Staff Software Engineer, Product (Remote - Belo Horizonte, Brazil)

Company: LawnStarter Location: Belo Horizonte, Brazil (Remote) Seniority: Senior Work Model: Remote Contract: Permanent Industry: Tech

About LawnStarter

LawnStarter is the leading on-demand marketplace for lawn care and outdoor services, facilitating over $100 million in annual bookings. We are expanding to become the go-to platform for all home services, operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a unified platform.

About Engineering at LawnStarter

Our engineering teams are small and focused, with Product Engineers working closely alongside Product Managers and Designers. You will be supported by an Engineering Manager dedicated to your professional growth. Collaboration with engineering peers across various initiatives within a shared codebase is integral to our process. The entire team shares ownership of the success metrics for their work.

We leverage AI coding agents as 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 impactful products to a real marketplace serving both customers and service providers.

The Role

As an engineering anchor for an initiative, you will be a key member of a close-knit team, collaborating with your Product Manager and Designer, and working alongside 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, deploying to production, and ultimately, owning the outcome with your team.

Your performance will be measured by impact, not just lines of code. When an AI agent can safely implement a solution, your role is to ensure it's done correctly and drives the desired metric. In areas requiring meticulous, hand-written code, you will be responsible for that implementation.

What Makes This Role Exciting:

• End-to-End Ownership: You will guide initiatives from problem definition through production deployment and post-launch metric review, owning the entire arc and its results with your team.
• True Product Partnership: You will collaborate directly with Product and Design, contributing engineering expertise to product decisions and product sensibility to engineering challenges.
• Autonomy with Support: You will have significant freedom in making technical decisions, with architectural reviews for major decisions and rapid input from peers.
• Staff-Level Impact: You are trusted to make critical decisions, deliver complex solutions, and stand behind the results.

What You'll Own:

• Technical Approach: Define the architecture, data models, integration strategies, rollout plans, observability, and rollback procedures for your initiative. You will make most decisions independently, seeking architect review for significant architectural choices, documenting them, and iterating based on data.
• Implementation Quality: Ensure the quality of AI-authored code through effective prompts, guardrails, evaluations, tests, and review processes. You are accountable for the code, held to the same high standards as if it were hand-written.
• Cross-Functional Partnership: Engage daily with your Product Manager on scope and tradeoffs, and 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 Product Manager 2-4 weeks post-launch, providing a clear assessment of success.
• High Shipping Bar: Maintain rigorous standards for production correctness, security, performance, observability, and the overall customer and pro experience. AI agents are accelerators, not compromises.

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, testing, and observability to ensure safety and quality.
• Owning Decisions with High Autonomy: Make and document technical decisions rapidly, balancing speed with alignment and accountability, with appropriate review checkpoints.
• Shipping Outcomes, Not Just Features: Focus on initiatives measured by specific metrics (e.g., conversion rates, retention, unit economics), ensuring scope is appropriate to move the needle and following up rigorously post-launch.

What Success Looks Like (Year 1):

• Successfully ship 3-4 initiatives end-to-end, with at least two demonstrably moving their target metrics.
• Develop and share effective AI agent workflows (prompts, evaluations, review loops) 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, with no customer- or pro-facing regressions attributable to AI-authored code slipping through review.
• Create visible, reusable artifacts (runbooks, evaluations, agent workflows, post