Senior Software Engineer, Data

We are building at the edge of what optimization software can do today.

Three of the problems on our table right now:

• Millions of customer records have to stay fast on screen while an optimization model runs over the same data
• The same data has to feed an interactive UI and a solver run, in different shapes, against different latency budgets
• A customer's numbers live across several systems in several formats. They have to arrive in one consistent shape, stay fast to query, and stay cleanly separated per tenant

There is no one here whose job is to break the work down for you. You take the data platform, you decide what it needs, and you own it end to end.

We build decision infrastructure for industrial companies. Our customers model their production, with its capacities, costs and constraints, and we compute the answer to "what should we do?" before the decision is made.

Our models decide how factories plan: what gets produced when, on which machine, and with how much stock. A planner acts on that answer, and it has to hold up in front of their management. The company measures the result in euros.

None of that works unless the data underneath is right, fast and complete. That part is this role.

Most optimization software fails in the same place. Not in the solver, but in the gap between what a company actually does and what the model assumes. Closing that gap is the whole company.

Founded by Dana (CEO) and Erik (CTO) out of RWTH research, backed by a €2.8M round led by Vorwerk Ventures, with customers live on our optimization models. A small team, based in Cologne.

Hi, I'm Erik, CTO of Circonomit. This ad is specific on purpose: you should be able to tell from it whether this is your job.

Scale our data platform across multiple customers and domains. Customer data arrives in many formats from many sources; it has to land consistently, stay manageable at millions of records, and be fast to query when models and results are on screen.

The product is a data-heavy web app with a math-heavy backend:
Python, Type Script, Solid.js, Postgres, on Cloudflare. Your center of gravity is data and infrastructure, and you touch the whole stack.

We will not sugarcoat it: short deadlines, real workload, and a platform that grows while customers already run on it.

Nobody here will keep your queue full. There are no tickets waiting for you.

• The data platform, end to end. Ingestion, storage, and the query paths that keep millions of records fast on screen. You design it, you build it, you run it in production
• The platform layer. Infrastructure and deployments. You make the path to production work; everyone else walks it themselves and owns what they ship
• Performance and correctness in the optimization engine
  , together with our research engineers
• The architecture of the data side. How this gets built is decided over the coming months, and whoever starts now decides it with us

Small team, no layers. You own the process to production: you decide when your work ships, you keep it running afterwards, and you are responsible for it.

Feedback runs both ways and continuously, in daily work and in weekly one‑on‑ones. We communicate proactively and flag it early when something isn't working. Saying no is part of the job.

We review each other's code, and we like being together in the Cologne office, because the fastest conversations still happen in a room.

Three of the problems on our table right now:

• Millions of customer records have to stay fast on screen while an optimization model runs over the same data
• The same data has to feed an interactive UI and a solver run, in different shapes, against…