Member of Technical Staff building agent investigation tools for Judgment Labs' continual learning infrastructure for long-horizon AI agents. Work covers a parallel-investigator agent, trace debugging and swarm UX, verification via simulated environments and replay, and platform features like workspaces, roles, and billing. Stack includes an SDK and terminal-first integration with Claude Code, Codex, and OpenCode; customer-facing and in-person in San Francisco.
Judgment Labs is building the infrastructure for continual learning in long-horizon AI agents.
We turn long agent trajectories into clean, structured data for evals, labeling, rubric generation, context engineering, and RL workflows. Instead of only showing teams what happened, Judgment helps decide what matters, what should be learned from, and how that learning should flow back into the agent.
Weโve raised $32M across two rounds led by Lightspeed.
You'll build the product experiences that make this loop legible, and you'll build the agents that run it. This is not a role where you implement specs handed down. You'll own problems end-to-end: talking to customers, defining what to build, building it, and iterating until it's great.