/roles — ROLE_141
Systems Engineer
Early-stage startup building fast-booting, stateful cloud computers for autonomous AI agents
The role
- COMP
- $180K - $300K
- EQUITY
- 0.5% - 1%
- LOCATION
- San Francisco
- WORKPLACE
- On-site
- EXPERIENCE
- 0 - 12 years
- VISA
- None, Visa transfers, New visa sponsorships
- STACK
- Rust, Go, C/C++, Kubernetes, Docker, AWS
- INDUSTRY
- AI, Software Development, Devtools, API SDK
The company
Early-stage infrastructure startup building fast, persistent virtual machines and tooling that let AI agents run continuously, keep state, and do production work.
- STAGE
- Series A-stage
- FUNDING
- $10M+ raised
- TEAM
- founding team of <10
- FOUNDED
- 2025
- BACKING
- VC-backed
JD — the work
About the role
The company gives AI agents persistent machines that boot in milliseconds, hold state, and run nonstop, and the engineering happens deep in the system: virtualization, kernels, file systems, storage, networking, and scheduling. On a small team of about ten, you would own whole subsystems and get them into production quickly, working directly with the CTO. The roadmap also reaches beyond cloud compute toward owned GPU hardware and infrastructure for training models.
What you'll do
- Build the sandboxing, isolation, and virtualization layers that let many tenants' agents run securely side by side
- Own subsystems such as storage, scheduling, networking, or virtualization from design through production
- Implement snapshot, restore, and durable state mechanisms for agents that never shut down
- Cut sandbox boot latency to a few tens of milliseconds, tuning syscalls and scheduler behavior along the hot path
- Create distributed storage, scheduling, and network layers designed for multi-region, global scale
- Measure before optimizing: benchmark, profile, and debug systems under realistic scale and correctness demands
- Contribute to future GPU cluster and training infrastructure work
What they're looking for
- Real depth in areas like kernels and operating systems, hypervisors, filesystems, or distributed systems
- Ownership of ambitious technical projects from start to finish, in industry, research, or open-source work
- Comfort working close to the metal on hypervisors, kernels, networking, and storage
- A portfolio of work others can inspect that proves real depth
Nice to have
- Hands-on experience building or running GPU infrastructure
- Background working on AI or ML systems
- Experience with distributed storage or consensus protocols