> Markdown version of [/jobs/ext/4625211-staff-engineer-ai-infrastructure-platform](https://www.wearedevelopers.com/jobs/ext/4625211-staff-engineer-ai-infrastructure-platform). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Engineer, AI Infrastructure & Platform - **Company:** Prime Inc. - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, C++ (Programming Language), Linux, Distributed Systems, Fault Tolerance, Open Source Technology, Software Systems, System Programming, Virtualization Technology, AI Infrastructure, Reinforcement Learning, Graphics Processing Unit (GPU) - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25197_a765210168a702aa3f8af4e20dfbfeb6 ## About the Role You have 5+ years of experience building production distributed systems from the ground up. You have strong systems programming experience. Production Go is a major advantage; Rust, C++, or comparable systems-language experience is also valued. You are a high-agency engineer who can lead the design and implementation of high-performance, fault-tolerant systems. You have strong Linux systems fundamentals and depth in at least one of virtualization, networking, storage, or workload isolation. You enjoy going deep on systems performance, whether the bottleneck is memory behavior, concurrency, networking, or resource utilization. You have built, deployed, and operated production systems at scale. ## Description Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own. Core Technical Responsibilities You'll build the distributed control plane and node-level runtime behind our sandbox platform: placing workloads across bare-metal workers, launching secure microVMs, and making the entire lifecycle fast, efficient, and resilient to failure. Build the control plane that places sandbox workloads efficiently across bare-metal CPU and GPU workers. Build node-level execution systems that launch and supervise secure microVMs, coordinate storage and networking, and take sandboxes from assignment to ready execution. Own the sandbox product surface, including its APIs, SDK, and CLI, and evolve it to support reinforcement learning and agentic workflows at scale. Work closely with research, applied research, customers, and the broader engineering team to take problems from discovery through design, implementation, and production adoption., You'll work alongside experienced engineers and researchers building core infrastructure for frontier AI research. You'll shape the sandbox platform that powers demanding reinforcement learning, evaluation, and agentic workloads, with opportunities to contribute to open-source infrastructure. On a small, high-ownership team, you'll help set technical direction and engineering practices while moving quickly from decisions to shipped systems. We value deep systems expertise and customer obsession. If you want to build foundational infrastructure from the control plane down to the node runtime, we want to talk to you.