Build production AI systems that automate scheduling, follow-up, and dispatch decisions for home service businesses.
AutoRev AI builds the AI coworker for home service businesses. It answers every call and text, books the job, follows up on every lead, and clears the busywork that keeps techs and dispatchers off the tools they already run. HVAC, plumbing, electrical, and roofing companies run AutoRev today to stop losing revenue to missed calls and slow follow-up.
This isn't a role for incremental features. You'll build the systems that decide how well AutoRev actually works for the businesses running it.
Every feature you ship affects whether a real business books more jobs or keeps missing calls. You'll see that impact directly, through usage and through what customers tell us, not through a roadmap review three quarters later.
This is early enough that a lot of the technical foundation is still being decided. What you build in the next year will still be running under the product long after.
Build and ship production AI systems that automate scheduling, follow-up, and dispatch decisions.
Ship features at a pace closer to weekly than quarterly.
Work directly with customers to understand their workflows and turn that into shipped code.
Integrate LLM and voice AI tooling into production systems.
Architect backend infrastructure that holds up as usage grows.
Own features end to end, from design through deployment.
Strong coding fundamentals. You're comfortable with hard technical problems and use AI coding tools as a real multiplier, not a crutch.
3-6 years of backend engineering experience, ideally at an early-stage startup.
A track record of building systems or products you're proud to talk about in an interview.
Able to get productive in an unfamiliar codebase within days, not weeks.
Bias for action. You ship fast without cutting corners that matter.
Product sense: you understand what a user actually needs, not just what was asked for.
You build systems that hold up under growth, not fragile quick fixes.
Comfortable with ambiguity and switching between problems quickly.
Experience with LLM-based or voice AI products in production.
Experience as an early or founding engineer.
You're joining while the technical foundation is still being built, so your architecture decisions matter for years, not months. The team is small enough that you shape how we build, not just what we build.
Book a demo to see the product our team is building, before you join us.