RL Environment Engineer

• Work directly with our research team on long-horizon RL environment and task creation for agent training, spanning many steps and hours of realistic effort rather than single-shot prompts

• Build and shape RL environments in your domain, including the setup, state handling, and tooling an agent interacts with

• Generate and refine ideas for tasks and agentic trajectories, then validate that the work is correct, hard, and covers the right edge cases

• Design reward functions, milestones, and rubrics that give meaningful signal across long trajectories, including partial credit where pass/fail is too blunt

Identify failure modes, reward hacking, and degenerate solutions before they reach training