Build realistic environments for AI agents and the infrastructure for RL training and benchmarking.
Location: Tübingen / Hybrid
Employment: Full-time
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.
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
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
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
Competitive compensation with equity
Flexible hours and a remote-friendly setup
Vacation, learning, and conference budget
Research freedom in a high-trust environment
Submit your CV, a short note, and links to work that shows how you think and build using the application form.
Job details are sourced from the employer's original posting.
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