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.