Agent Maestro role to build multi-agent orchestration that assigns PM, coder, QA, and deployer agents to tasks, plus self-healing workflows that detect and escalate blocked agents. Also covers building evaluation and benchmarking systems and experimenting with models and agent frameworks. Requires 3+ years of engineering experience, at least 1 year focused on AI/LLM applications, and Python, TypeScript, or Ruby fluency.
Superconductor is building the autonomous software organization β a platform where agents don't wait for instructions, but find work everywhere: in customer emails, bug reports, session replays, Slack threads, X posts, etc. Agents that work while you sleep.
We're a team of 7, backed by $7M in funding, and we intend to stay below ~25 humans hopefully forever. That means every hire matters enormously, and we compensate accordingly with highly competitive salary and equity.
We have been building software together for over a decade. We formerly co-founded Gradescope, an AI-powered education grading platform used by millions of students worldwide. Previously, we were AI PhD students at UC Berkeley. All in all, we are four developers, one designer, and two generalist operators, and we all wear multiple hats every day.
You live and breathe AI agents. You've tried every coding agent harness, and you have strong opinions about what works and what doesn't. You spend your weekends experimenting with agent orchestration frameworks, MCP servers, and multi-agent workflows.
We have less of a clear idea for what this role entails than for our other open roles. Things move so fast that the main attribute weβre looking for is raw intelligence, boundless energy, and an extreme eagerness to learn something new every day.
In your first month, you might take Superconductor to #1 on Terminal-Bench. Or you might use our platform to rebuild a major piece of software in days. Or youβll develop and evaluate a novel agent orchestration framework. Or you might build something else we haven't imagined yet β pitch us on it!