Founding Engineer

About Us

We believe the next generation of home services companies will run on technicians + AI. Humans will do the work in the field and an AI company brain will run the business around them.

Serve is building that AI brain, starting with pest control, a $30 billion global industry. We’re bringing frontier AI to the work that keeps these businesses running: winning customers, scheduling jobs, coordinating technicians, collecting payments, and keeping customers happy for years.

We already closed 6 figure annual contracts with enterprise customers whose support operations cost millions per year. Our software is live, handling critical operations and improving our customers’ bottom lines. We raised our seed round from investors including General Catalyst, NFX, Goodwater Capital, and experienced operators.

We’re hiring a founding engineer with the judgment skills to decide what we should build and the technical depth to make it work. You’ll work directly with the founders and customers and will shape the product, the architecture, and how we build.

What you’ll build

Our goal is a system that understands a business well enough to run it on its own. You will work on everything from applied AI, fullstack engineering, and customer deployments. Projects include:

• A personal AI concierge that knows every customer. Build agents that remember a home’s history from years of service and anticipate each house’s needs to follow through with them. You’ll work on AI memory, reasoning, tool use, and knowing when to bring in a human in the loop.

• ML models from real-world ops data. Build prediction and optimization systems that improve as they learn from outcomes. For example, decide which technician should visit which home in what order while optimizing for low gas costs, travel time, and prioritizing perceived job urgency.

• A sales engine that autonomously closes deals. Use customer history and 100+ data points to decide whom to contact, when to do it, and what to offer. Build personalized outreach campaigns and run experiments to measure which decisions generate additional revenue.

• Evals that make the product stronger. Turn production traces into test cases, simulations, and benchmarks. Compare models and approaches on accuracy, task completion, latency, cost, and business results. Follow the evidence wherever it leads, from a different model to a better interface or a simpler workflow.

• Integrate AI into more of our customers’ business, and into new industries. Expand Serve into work such as accounting, procurement, and inventory. Bring the platform to other home services industries. Work with the first customers in each market, learn how they operate, and decide what to build, what to reuse, and what needs a different approach.

What you’ll own

Be comfortable getting on a plane and spending a week at a customer’s headquarters. Sit with their team, understand their work, learn the exceptions, and find the problems that are a bottleneck to their growth.

Then own the solution by deciding the scope, designing the system, writing the code, launching it, and measuring the results. You’ll lead deployments as we grow into seven-figure annual contracts, with responsibility for systems that can unlock millions in annual revenue for Serve and our customers.

Every deployment should make the platform stronger.

What we’re looking for

• Strong engineering fundamentals. You’ve shipped software people rely on at scale. You can design systems, work across the backend and frontend, and debug difficult problems in production. You understand and can vocalize the tradeoffs behind your decisions.

• Sharp product judgment. You can discover the problem behind a customer’s request, decide what matters, and build something that feels simple to use. You have a point of view and change your mind when the evidence calls for it.

• Deep understanding of applied AI. You’ve built with LLMs and understand context, retrieval, tool use, and evaluation. You can diagnose why an agent fails, design experiments to improve it, and weigh the gains against latency and cost. You keep up with new methods and can judge which ones are useful.

• Clear communication. You ask precise questions and explain complex ideas simply. You can lead a customer conversation, work through a technical disagreement, and keep people informed when a plan changes.

Nice to have

• Experience as a founder, founding engineer, or early employee building a product from its first customers.
• Experience leading enterprise deployments, integrating with legacy systems, or working on-site with customers.
• Technical depth in voice AI, prediction, optimization, or systems that learn from production data.

Benefits

• Health, dental, and vision insurance
• 401(k) with company match
• Unlimited PTO
• Lunch on us in the office
• Monthly gym membership reimbursement
• Monthly reimbursement for AI tools and productivity software

Our interview process

• Send us any relevant information (resume, background, github) and the most impressive thing you’ve built

• Interview with Kamal (CEO): Talk about what we’re building, what you’ve built, and what you want to do next.

• Interview with Anthony (CTO): Walk through a project you owned, including the architecture, tradeoffs, and lessons from production. Then work through a Serve customer problem together.

• In person technical interview: Work on a scoped technical problem where you understand a problem, build a working piece of the solution, and show how you’d evaluate it. Use your usual tools, including AI coding assistants.

• References and offer conversation. Answer the remaining questions on both sides.