Engineering Manager (AI-First Leadership) - LawnStarter

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About Engineering at LawnStarter

Our engineering team builds the platform connecting hundreds of thousands of homeowners with over 70,000 active service pros across three brands (LawnStarter, Lawn Love, HomeGnome) on shared infrastructure. We are profitable and growing, shipping constantly with end-to-end ownership. Strong processes and engineering managers exist, so you’re raising the bar, not building from scratch.

The Role

We’re scaling, requiring engineering leadership to support new initiatives. You’ll lead cross-functional teams of 4–5 engineers, reporting to the Head of Engineering. Your focus: ensuring your team ships reliably, grows professionally, and avoids bottlenecks as LawnStarter expands into new service verticals.

This is a people-first role. If your identity as an Engineering Manager (EM) is primarily technical—preferring architecture reviews over underperformer management—this isn’t the right fit. If you excel at articulating team performance in metrics, handling conflict directly, and developing engineers, keep reading.

What Makes This Role Unique

• You’ll own both delivery and people outcomes—neither can be delegated.
• Distributed team across time zones; async leadership and written communication are critical.
• We move fast and ship—you’ll feel the difference between a humming team and a stuck one.
• AI-forward is not a buzzword; you’ll lead your team in adopting AI tools and workflows.

What You’ll Own

• People Development: Concrete growth plans for every individual contributor (IC) on your team. You’ll know where each person is headed and what it takes to get there.
• Delivery: Your team ships on predictable cadence with high-quality output. You’ll surface risks early, manage scope, and avoid missed commitments.
• Team Health: Conflict is addressed directly. Underperformers are managed with a clear process. Top performers are protected and developed.
• Cross-Functional Partnership: Interface between your team and Product, Design, and other engineering teams. Decisions are made, not stalled.
• Technical Direction: Close enough to the work to provide architectural input and catch risks, but not so close that you’re bogged down in day-to-day tasks.
• AI Adoption: Actively introduce AI tools and workflows into your team’s operations, such as code review, documentation, sprint planning, and debugging.

Problems to Solve

• Building People Leadership Depth: As LawnStarter scales into new service verticals, you’ll develop the next generation of senior engineers and tech leads—not just ship features.
• Managing Distributed Teams: Our team spans multiple time zones and countries. Async communication, remote 1:1s, and distributed sprint ceremonies are the norm. You’ll need to build trust without shared physical space.
• Turning Delivery Consistency into a Competitive Advantage: We have product-market fit and momentum. Your team’s velocity and predictability directly impact LawnStarter’s ability to launch new services and capture market share.
• Orchestrating Cross-Functional Delivery: You’ll act as the connective tissue between Product, Design, and specialist functions (quality engineering, architecture, security) from estimation through delivery.
• Turning AI Adoption into Throughput: We’re not experimenting with AI on the margins. You’ll lead your team in adopting AI tools like Claude Code, spec-driven development, and AI-assisted review, ensuring measurable throughput without sacrificing quality.

What Success Looks Like (Year 1)

• Every engineer on your team has a documented growth plan within 60 days, and you can speak to it from memory.
• Your team ships its committed scope on cadence within 90 days.
• Zero surprise departures—you’ll know your retention risks and actively address them.
• Underperformance is addressed directly and documented, not deferred.
• The Head of Engineering trusts your team’s commitments because you’ve proven they’re reliable.
• Your team is visibly more AI-enabled than when you joined, with new tools adopted and manual tasks automated.

Requirements

Who You Are:

• Deeply AI-integrated: You’ve moved past basic AI usage (e.g., using ChatGPT for emails). Your engineers expect you to introduce AI workflows, such as using Claude for code review or Copilot in development. You’re actively experimenting, sharing results, and setting the pace for AI adoption.
• A people developer: You can provide concrete examples of career growth plans, hard conversations, and structured underperformance management. Your 1:1s focus on people, not status updates.
• Remote-native: You’ve led fully remote teams as a default, not just during COVID. You know how to build trust, run async decision-making, and prevent isolation.
• Direct in conflict: You address tension directly and quickly, whether it’s between engineers, engineering and product, or performance expectations.
• Data-driven: You articulate team performance in metrics (velocity, retention risk, IC growth) and use data to make decisions.
• Technically credible: You stay close enough to the code to earn your team’s respect, providing input on architecture and debugging under pressure.
• A delegator: You build a team that makes good decisions without you, coaching engineers toward answers rather than providing them.

This Role Is NOT:

• A pure technical architect role—your focus is on team effectiveness and growth.
• A process manager—your job is to lead people running processes, not document them.
• A stepping stone—you’re committed to people leadership as your primary craft.
• A reactive firefighter—you surface risk early and manage it proactively.
• An AI skeptic—you actively drive AI adoption on your team.

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