Build realistic environments for AI agents and the infrastructure for RL training and benchmarking. Location: Tübingen / Hybrid Employment: Full-time The role You will build the environments and benchmarking systems at the core of our products.

The role combines strong software engineering with practical work on AI agents: designing realistic environments, investigating agent behavior, and making evaluations reliable and useful. You will work across these problems with the rest of the team, with a particular focus on software architecture, infrastructure, and implementation.

What you’ll work on Build and maintain production software systems and realistic environments for AI agents Develop reliable backend and cloud infrastructure for RL training and benchmarking Turn research prototypes into dependable tools and products Improve developer workflows across backend, data, and machine-learning systems What we’re looking for Strong software-engineering fundamentals and a record of shipping systems end to end Experience with backend development, infrastructure, or distributed systems Good judgment in ambiguous projects and the ability to choose practical designs Interest in AI systems and working across engineering and research Useful experience Early-stage startup or small-team product development LLM APIs, agent systems, or ML platforms Cloud infrastructure, containers, queues, or distributed workloads Developer tools, evaluation platforms, or data-intensive applications What we offer Competitive compensation with equity Flexible hours and a remote-friendly setup Vacation, learning, and conference budget Research freedom in a high-trust environment Work with us Submit your CV, a short note, and links to work that shows how you think and build using the application form.