We're looking for a founding engineer. This isn't a "join a team" role. It's a "build the team" role. You'll work directly with the founders in a radically transparent environment, no layers, no politics, on a company early enough that what you decide now is how it works for years.
You'll ship product, shape architecture, build the agents, sit with the engineering leaders who use them, and define what engineering excellence looks like here before there is a definition. Some weeks that means going deep in our code. Some weeks it means being the person in the room with a CTO.
We are an AI-heavy company, and we mean it. AI isn't a feature we're adding: it's how we build. We use AI tools aggressively to multiply what a small team can do, and we expect you to push that boundary further. If you've been frustrated by how slowly most teams move, you'll feel at home here.
Responsibilities
Ship product end-to-end. From data ingestion pipelines to the interface customers interact with daily. You own features from idea to production.
Build the agents. Active agents that attach to a pull request, a release or an incident and act on their own. Reflective agents that find the pattern across a hundred sessions or a month of review comments, then propose the change for a human to decide.
Set the engineering bar. Define the practices, tooling, and culture that let a tiny team operate at 100x. Embed AI deeply into how we develop software.
Talk to customers. Understand what engineering leaders actually need. Your technical depth will directly influence our product roadmap and help close deals.
Shape the founding team. Help us hire the next engineers and set the cultural DNA that attracts world-class talent.
Requirements
You've built and shipped products at startups where speed and ownership were non-negotiable.
You're a strong full-stack engineer who can go deep on backend infrastructure and ship clean frontend when the team needs it.
You use AI to multiply your own productivity as a core part of how you work every day. You have strong opinions about how AI is changing the way small teams build software.
You have made something happen with no spec, no process and nobody to ask. Ambiguity is where you do your best work, not where you stall.
You give and receive direct feedback well. You care more about getting it right than being right.
Our Culture
We are seven people in one office in Berlin, together every day, and you would be the fifth engineer. There is no layer between you and any decision. Outside of engineering, you hear the customer call happening across the room, you turn around to ask a founder what it means, and you are there when we decide what to do about it, whether or not it is your area. Nothing important here gets settled somewhere you are not.
A room like that only works if everyone in it is honest. We are ambitious and curious and relentless about getting to the right answer, we make the hard calls quickly, and we don't let things linger. We're not optimizing for one part of the company either. We want the whole thing to be remarkable: the product, the engineering, the customer experience, the way we treat each other.
Which is why we argue hard about ideas and stay careful with each other. That's not a soft statement. It's a filter, and we use it: no brilliant jerks, however good the work. It is the first thing people notice here and the reason the hard parts become easy. We're building a team we're proud of, and the product comes out of that. That's the bar.
Why the company
A real problem, real customers. You would not be building for a hypothetical user. Engineering leaders are inside this product every week, and they say plainly when something hasn't changed their day.
The frontier, on purpose. Two of the problems on your desk: ephemeral environments that let an agent spin up an entire application, and making a new agent cheap enough that an engineer who has understood a job can have a first version running against a customer in a day.
Outsized impact. A small team pointed at real scale. Something you build this month is running inside engineering orgs of more than a hundred people before the quarter is out.
The agents you build are the ones you need. We run the company on the company. If it isn't good enough for us, it isn't good enough to ship.
Skills: Kubernetes, Python, LLMs, Fine-tuning, Evals, AI Agents