Senior Software Engineer, Agentic Infrastructure

At Relativity Space, we’re building rockets to serve today’s needs and tomorrow’s breakthroughs. Our Terran R vehicle will deliver customer payloads to orbit, meeting the growing demand for launch capacity. But that’s just the start. Achieving commercial success with Terran R will unlock new opportunities to advance science, exploration, and innovation, pioneering progress that reaches beyond the known.

Joining Relativity means becoming part of something where autonomy, ownership, and impact exist at every level. Here, you're not just executing tasks; you're solving problems that haven’t been solved before, helping develop a rocket, a factory, and a business from the ground up. Whether you’re in propulsion, manufacturing, software, avionics, or a corporate function, you’ll collaborate across teams, shape decisions, and see your work come to life in record time. Relativity is a place where creativity and technical rigor go hand in hand, and your voice will help define the stories we’re writing together. Now is a unique moment in time where it’s early enough to leave your mark on the product, the process, and the culture, but far enough along that Terran R is tangible and picking up momentum. The most meaningful work of your career is waiting. Join us.

Dark Matter Lab is a research group within Relativity Space focused on advanced aerospace systems, agentic engineering, and technologies outside the conventional roadmap. We build the infrastructure needed to turn new ideas into engineering capabilities people can actually depend on.

We run a stack of interconnected agentic systems — SybilClaw, yapCAD, Mechatron, Multigraph, local LLM inference, an inter-agent message bus, parametric CAD pipelines, a print farm, and the infrastructure connecting it all. We need an engineer who can own and evolve these systems as they move from prototypes into production engineering infrastructure.

This role is for someone who has deployed an agentic harness (OpenClaw, Hermes, SybilClaw, or something comparable) in a real work environment. You understand what it takes to make these systems reliable when engineers depend on them every day. You’ll learn the stack, improve it, and work with forward-deployed engineers to package portions of it for deployment with internal and external customers.

• Own the reliability of our agentic infrastructure: agents, sessions, model routing, context pipelines, inter-agent communication, and supporting services

• Build and maintain infrastructure where good off-the-shelf solutions don't yet exist

• Deploy and operate local LLM inference across Mac Studio and GPU hardware

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