Remote Jobs (Work From Home)

This is a remote role for candidates located in So 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:

• You ship end-to-end. From problem-framing through production to the post-launch metric review you see the whole arc and own the result with your team.
• You work as a true product partner. You sit at the table with PM and design, bringing engineering judgment to product calls and product sense to engineering calls.
• You get real autonomy with the right checkpoints. You make most technical calls yourself, with architect review on significant architectural decisions and fast input from peers.
• You operate at a staff bar. You’re trusted to make the call, ship the hard thing, and stand behind the outcome.

What You’ll Own

• The technical approach architecture, data model, integration choices, rollout plan, observability, and rollback strategy for your initiative. You make most calls yourself and bring significant architectural decisions to architect review; you document them, and revisit if the data says you were wrong.
• Implementation quality the prompts, guardrails, evals, tests, and review loop that let agents ship safe, correct, production-ready code. Most lines will be agent-authored, and you’re accountable for them held to the same standard as the rest of the team working in a shared codebase.
• Cross-functional partnership daily working contact with your PM (scope, tradeoffs) and designer (UX decisions, in-tool prototyping), regular collaboration with engineering peers, and weekly check-ins with your EM.
• The initiative outcome the metric the initiative was set up to move. With your PM, you present results 24 weeks post-launch and share the “did it work” answer.
• A high bar for what ships production correctness, security, performance, observability, and the experience for customers and pros. Agents accelerate you; they don’t lower the bar.

Problems to Solve

Leading AI agents at a staff-level quality bar Most of the code on your initiative will be authored by AI agents. The craft is making them ship as if a senior engineer wrote it: prompts that encode our conventions, evals that catch issues before merge, tests that exercise the edges, observability that catches a regression before a customer does. How do you build a workflow that lets a small team ship far more than its size would suggest?

Owning decisions with high autonomy You have real latitude to make and document technical calls quickly with architect review on the big architectural ones and peers to pressure-test your thinking. How do you move fast, keep your team aligned, and stay accountable to the outcome?

Shipping outcomes, not features Each initiative is measured by a metric a conversion rate, a retention curve, a pro-funnel KPI, a unit-economics shift. You’re accountable for the number alongside your team. How do you scope to actually move it, decide what *not* to build, and have the discipline to follow up 24 weeks after launch?

What Success Looks Like (Year 1)

• Initiative outcomes hit You’ve shipped 34 initiatives end-to-end, and at least two clearly moved their metric (with the post-launch review to prove it).
• Agent workflow that travels The prompts, evals, and review loop you built are picked up by peers on other initiatives.
• Faster cycle time Median time from problem-framing to first production rollout on your initiatives is meaningfully shorter.
• Quality holds No customer- or pro-facing regression traceable to agent-authored code that slipped through your review.
• Visible leverage Peers point to artifacts you left behind runbooks, evals, agent workflows, post-launch write-ups as references they use.

Requirements

Who You Are

• AI-native. Claude Code, Cursor, Codex, or equivalent are how you ship today daily, on production work. You have real opinions about prompts, evals, agent loops, and review workflows, and you know when to let the agent run versus write it yourself.
• Operating at a lead level. Whatever 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 in “did the metric move” and “did the experience get better.” You read the post-launch dashboard and own the answer.
• A strong horizontal partner. You hold your own with a strong PM and designer, and you collaborate well with 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, write them down, get fast input, and move.
• A force multiplier. Your impact compounds beyond your own initiative because you leave reusable artifacts behind agent workflows, evals, runbooks, post-launch reviews.
• Customer- and pro-minded. This is a real marketplace with real people on both sides, and you care about the outcomes for both.

Good to Know

• An individual-contributor role with room to grow. People management sits with the EM but the path into management is an open door for those who want it.
• A product-engineering role, end-to-end. You ship features that move metrics; platform and architecture work happen inside the initiative when the outcome needs them.
• Hands-on, with a high quality bar. Agents handle much of the implementation; you bring the judgment, design, safety, and accountability. The bar is high.
• Shipping to a live marketplace. 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
• 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.

Benefits

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

Here at Clerky, we build software to make legal paperwork easier for startups and their attorneys. We’re profitable and growing sustainably. We’re the most popular way for high-growth technology startups to form, and are also used by many top-tier startups for hiring and fundraising.

As a Customer Operations & Writing Specialist at Clerky, you will be the voice of the company to thousands of startup founders, investors, and attorneys. These customers use Clerky to get critical legal paperwork done, often on a tight timeline. Our success is based on word-of-mouth, so we have a strong culture of providing world-class service (ask us about our satisfaction ratings!). We are rabidly customer-centric.

What Makes Customer Operations Different at Clerky

Its a lot harder here. Helping our customers can be unusually challenging due to the nuanced and specialized nature of their questions. Doing the job well can require a lot of iterative feedback, so we’re looking for someone who thinks critically about their writing and is always looking for ways to improve. Along the way, you’ll also pick up a lot of knowledge about startups and startup law.

The challenges never stop. The level of learning and craftsmanship that goes into writing responses to our customers requires intense focus. If youre looking for the kind of position where you can easily master all the information at the beginning and work in a way that does not require intense focus, this position will probably not be a good fit for you. On the other hand, if you love learning and constantly challenging yourself, this position could be a good fit for you.

There are often no right answers. Were often not able to provide definitive answers to the questions we receive. In many cases, the best we can do is to equip our customers with the information they need to be able to figure out the right answer on their own, or to understand that it isnt possible to figure out what the right answer is. If you prefer an environment more oriented around providing definitive answers, this position may not be a good fit for you.

• Genuine love for helping people

• High emotional intelligence

• Logical / analytical thinker

• Exceptional written English communication skills, including the ability to write precisely and succinctly

• Extremely detail-oriented

• Comfort with working remotely and independently

• Technologically savvy – you should be confident in your ability to use new software without training

• Appreciation for giving and receiving feedback often (often several times a day)

• Natural internal motivation to constantly strive for excellence in everything you do

• Clerky has been remote-first for many years, long before COVID. Were very familiar with working remotely, and enjoy it.

• Our team is small, so everyone’s contributions matter. We work efficiently, autonomously, and with great respect for each other.

• We work openly and collaboratively. Were here to support you in being successful in this role. You’ll work closely with other team members to ensure our customers are getting the best possible support and experience.

• Everyone on our team works hard, and we trust team members to know what will help them be most productive. Schedules are flexible as long as there is adequate team coverage.

• We want to help you grow, so we have a budget for books, courses, tools, or whatever other educational resources you need to be successful.

• We offer top-of-market compensation and benefits and the opportunity to learn a lot while helping our customers through an exciting time in their lives.

• Writing thoughtful and empathetic replies to customer emails using our help desk software, Help Scout

• Writing and maintaining help center articles, and identifying topics for new articles based on customer inquiries

• Working with our engineering team to debug software issues our customers encounter

• Using our software to develop and manage new ways for our customers to complete legal paperwork

• Assisting product team by testing new features and bug fixes, and conveying customer feedback

• Spotting trends in customer issues that other team members should be alerted to

This is a 100% remote position. You’ll be able to work from home (or from anywhere else). We offer top-of-market compensation and benefits, reasonable hours, and reasonable customers. No legal experience or background is necessary or preferred.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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:

• You ship end-to-end. From problem-framing through production to the post-launch metric review you see the whole arc and own the result with your team.
• You work as a true product partner. You sit at the table with PM and design, bringing engineering judgment to product calls and product sense to engineering calls.
• You get real autonomy with the right checkpoints. You make most technical calls yourself, with architect review on significant architectural decisions and fast input from peers.
• You operate at a staff bar. You’re trusted to make the call, ship the hard thing, and stand behind the outcome.

What You’ll Own

• The technical approach architecture, data model, integration choices, rollout plan, observability, and rollback strategy for your initiative. You make most calls yourself and bring significant architectural decisions to architect review; you document them, and revisit if the data says you were wrong.
• Implementation quality the prompts, guardrails, evals, tests, and review loop that let agents ship safe, correct, production-ready code. Most lines will be agent-authored, and you’re accountable for them held to the same standard as the rest of the team working in a shared codebase.
• Cross-functional partnership daily working contact with your PM (scope, tradeoffs) and designer (UX decisions, in-tool prototyping), regular collaboration with engineering peers, and weekly check-ins with your EM.
• The initiative outcome the metric the initiative was set up to move. With your PM, you present results 24 weeks post-launch and share the “did it work” answer.
• A high bar for what ships production correctness, security, performance, observability, and the experience for customers and pros. Agents accelerate you; they don’t lower the bar.

Problems to Solve

Leading AI agents at a staff-level quality bar Most of the code on your initiative will be authored by AI agents. The craft is making them ship as if a senior engineer wrote it: prompts that encode our conventions, evals that catch issues before merge, tests that exercise the edges, observability that catches a regression before a customer does. How do you build a workflow that lets a small team ship far more than its size would suggest?

Owning decisions with high autonomy You have real latitude to make and document technical calls quickly with architect review on the big architectural ones and peers to pressure-test your thinking. How do you move fast, keep your team aligned, and stay accountable to the outcome?

Shipping outcomes, not features Each initiative is measured by a metric a conversion rate, a retention curve, a pro-funnel KPI, a unit-economics shift. You’re accountable for the number alongside your team. How do you scope to actually move it, decide what *not* to build, and have the discipline to follow up 24 weeks after launch?

What Success Looks Like (Year 1)

• Initiative outcomes hit You’ve shipped 34 initiatives end-to-end, and at least two clearly moved their metric (with the post-launch review to prove it).
• Agent workflow that travels The prompts, evals, and review loop you built are picked up by peers on other initiatives.
• Faster cycle time Median time from problem-framing to first production rollout on your initiatives is meaningfully shorter.
• Quality holds No customer- or pro-facing regression traceable to agent-authored code that slipped through your review.
• Visible leverage Peers point to artifacts you left behind runbooks, evals, agent workflows, post-launch write-ups as references they use.

Requirements

Who You Are

• AI-native. Claude Code, Cursor, Codex, or equivalent are how you ship today daily, on production work. You have real opinions about prompts, evals, agent loops, and review workflows, and you know when to let the agent run versus write it yourself.
• Operating at a lead level. Whatever 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 in “did the metric move” and “did the experience get better.” You read the post-launch dashboard and own the answer.
• A strong horizontal partner. You hold your own with a strong PM and designer, and you collaborate well with 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, write them down, get fast input, and move.
• A force multiplier. Your impact compounds beyond your own initiative because you leave reusable artifacts behind agent workflows, evals, runbooks, post-launch reviews.
• Customer- and pro-minded. This is a real marketplace with real people on both sides, and you care about the outcomes for both.

Good to Know

• An individual-contributor role with room to grow. People management sits with the EM but the path into management is an open door for those who want it.
• A product-engineering role, end-to-end. You ship features that move metrics; platform and architecture work happen inside the initiative when the outcome needs them.
• Hands-on, with a high quality bar. Agents handle much of the implementation; you bring the judgment, design, safety, and accountability. The bar is high.
• Shipping to a live marketplace. 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
• 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.

Benefits

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

• Develop and maintain public API features and open-source SDKs for running customer-provided jobs on our quantum hardware and simulators.
• Develop and maintain infrastructure for automating system tuning and calibration.
• Develop and maintain software for scheduling the execution and analyzing the results of quantum algorithms.
• Work closely with our Quantum Engineers to write idiomatic, tested and extensible code for executing experiments and algorithms on our quantum hardware.

• BS or MS in Computer Science, Computer Engineering, or equivalent.
• Minimum 5 years of post-degree professional experience as a software engineer.

• A passion for writing software and a track record of implementing architecture level features in complex computer systems.
• Proficiency with Python and SQL. Experience with a compiled language such as C++ or Rust is preferred.
• Familiarity with Git version control, automated testing, and software development best practices.
• Willingness to learn atomic, optical, laser physics, and quantum mechanics concepts required to put work in context.
• Experience with Azure, AWS and Terraform, Javascript, UI/UX design for webapps, and a background in physics are welcome, but not required.