We are hiring a Systems Engineer for an early-stage AI infrastructure startup in San Francisco building the compute substrate for autonomous AI agents. The team works at the deepest layers of the stack: virtualization, operating systems, kernel internals, file systems, distributed storage, networking, scheduling, and orchestration.
What we're looking for
We need a systems engineer with depth in OS/kernel internals, virtualization, file systems, or distributed infrastructure who has owned technically ambitious projects end-to-end in production, open source, or research. You should be comfortable working at the lowest layers of the stack (kernel, hypervisor, storage, networking) and have a verifiable body of work that demonstrates genuine depth. Bonus points if you have experience with GPU infrastructure, AI/ML systems, or distributed storage/consensus.
What you'll do
Build core compute and runtime primitives for long-running, stateful AI agents, including virtualization, sandboxing, and isolation systems for secure multi-tenant workloads.
Take ownership of entire subsystems end-to-end (storage, scheduling, networking, virtualization) and ship them to production at a small team where your work matters immediately.
Work closely with leadership and the engineering team to design and implement persistent state, snapshotting, and recovery mechanisms for always-on agent workloads.
Reduce sandbox startup latency to sub-50ms and optimize performance across every syscall and scheduling decision in the critical path.
Design and build distributed storage layers, schedulers, and networking infrastructure that will scale across data centers globally.
Profile, debug, and benchmark systems under real-world scale, latency, correctness, and reliability constraints, measuring before optimizing, then optimizing relentlessly.
Contribute to the longer-term roadmap including on-prem GPU clusters and model training infrastructure as the company expands beyond cloud compute.
0 to 12 years of experience. New grads welcome; experienced hires (3-6+ years) also valued.
Full-time, 5 days per week on-site in San Francisco, CA. Relocation support available (flights and 6 months rent covered). Open to visa transfers and visa sponsorship for candidates already in the US.
Tech stack: Rust, Go, C, C++, Linux, KVM, Firecracker, hypervisors, virtualization, Kubernetes, Docker, distributed systems, file systems, operating systems, kernel development, CUDA, GPU infrastructure, AWS EC2, networking, storage systems.
- Depth in OS/kernel internals, virtualization, file systems, or distributed infrastructure
- Owned technically ambitious projects end-to-end in production, open source, or research
- Comfortable working at the lowest layers of the stack (kernel, hypervisor, storage, networking)
- Verifiable body of work that demonstrates genuine depth
- Bonus: experience with GPU infrastructure, AI/ML systems, or distributed storage/consensus
- 0 to 12 years of experience; new grads welcome
- Base salary with meaningful equity (0.5% - 1%) and bonus compensation
- Relocation support: flights and 6 months rent covered
- Open to visa transfers (e.g. OPT, H1B transfers) and visa sponsorship for candidates already in the US
- Full-time on-site role with high ownership on a small, talent-dense engineering team