About the role
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.