If AI is just a tool you use to code faster, save your time — this isn’t the job. If you think AI is the substrate every software job is being rebuilt on, keep reading.

We’re hiring a proper engineer. Someone who can ship production code, hold strong opinions about architecture, and care about scale and security. We’re a small team, so you’ll do everything — from frontend to infra. The job is delivering production code with AI and sharpening the AI-native pipeline that ships it — real-time AI, in production, at scale.

Now the catch, and we’d rather say it up front than dance around it: part of your job is to automate your job away. Not as a layoff plan. As a career plan. The engineers who win at Atender are the ones who keep making the version of themselves who walked in the door obsolete, because that’s how you free your hands for the harder, more interesting work upstream. We think it’s the only honest way to work with AI in 2026, and we want teammates who agree.

In practice that looks like running five to ten agents in parallel on a normal day, background agents working while you sleep, and a constant hunt for the next task you can hand off. The efficiency chase is the job — keeping agents busy at all times, spinning up more, pushing the leverage further. If that’s already how you work, you’ll feel at home fast.

You can work from anywhere. Pick a home office, pick one of ours, mix the two — your call. The one non-negotiable: you’ll travel to meet the team in person on a regular cadence. Some things still happen better in a room.

Bonus points if you’ve worked on the customer service side at some point in your life. Picking up a phone, working a queue, defusing an angry email — it changes how you build for the people who do that every day. You don’t need to have done it for years.

What we’re looking for

• A CS degree, or the self-taught equivalent — proven by what you’ve shipped.

• You’ve run distributed systems in production: queues, workers, retries, idempotency.

• You own your code past merge — AI-native CI/CD and observability that catches problems before customers do.

• Strong backend fundamentals: databases, caching, and security and data isolation in multi-tenant systems.

• You move at the pace of the field — current on the latest in AI, and always trying the next tool.