Build and optimize infrastructure, developer tooling, build systems, CI/CD, APIs, services, and deployment platforms. Investigate performance bottlenecks across software, operating systems, storage, networks, and hardware; improve observability, reliability, provisioning, and recovery. Develop internal platforms used by multiple engineering teams, maintain homelab infrastructure, and measure the impact of performance and workflow improvements.

Build low-level infrastructure for persistent, autonomous AI agents, including virtualization, sandboxing, storage, scheduling, networking, runtime systems, recovery, and performance tooling. Responsibilities include designing production systems, debugging complex failures, optimizing latency and resource usage, and ensuring reliability, correctness, and secure multi-tenant isolation. The role requires end-to-end ownership, strong systems fundamentals, and collaboration in an in-person San Francisco environment.

Paid, full-time infrastructure engineering internship focused on distributed systems, persistent compute, storage, scheduling, orchestration, virtualization, networking, reliability, observability, and production AI-agent infrastructure. Interns will own and ship meaningful projects, write production-quality code and tests, investigate failures, and communicate architectural tradeoffs. The role is approximately three months, fully in person in San Francisco, with potential relocation and visa support depending on circumstances.