Infrastructure Engineer Intern

Dedalus Labs, Inc. • San Francisco, CA

10h • Onsite

About The Position

Dedalus Labs is an AI research neolab building infrastructure for AI agents. We’re building the persistent compute layer that powers the next generation of autonomous software. Our platform spans distributed storage, virtualization, orchestration, networking, scheduling, and runtime infrastructure for long-running AI agents. We’re looking for unusually high-potential engineers who want to learn how reliable systems are designed, built, broken, and improved.

This is a paid, full-time, approximately three-month internship based in San Francisco. Applications remain open on a rolling, year-round basis. When we meet an exceptional or unusually high-slope engineer, we can invite them to join the team for a season.

You’ll work directly alongside Dedalus engineers on real infrastructure, not a disconnected intern project. You may shadow experienced engineers, but you’ll also be expected to take ownership, write production-quality code, investigate difficult problems, and explain your decisions.

Interns who demonstrate exceptional technical ability, judgment, ownership, and mutual fit may be considered for full-time roles.

Requirements

• A public GitHub profile is required.
• Demonstrated programming ability in Rust, Go, C, C++, or a similar language.
• Evidence that you have built and completed technically meaningful projects.
• Solid computer-science fundamentals and a genuine interest in systems.
• The ability to reason clearly about tradeoffs, failure modes, and debugging.
• Specificity about what you personally built and why you made particular decisions.
• High agency, intellectual honesty, curiosity, and learning velocity.
• Strong written and verbal technical communication.
• The ability to work full-time and in person from our San Francisco office for approximately three months.
• A specific reason you want to work on infrastructure for AI agents at Dedalus.
• Students, recent graduates, researchers, self-taught engineers, open-source contributors, and early-career engineers are all welcome to apply.

Nice To Haves

• Experience with distributed storage systems.
• Familiarity with consistency models, consensus algorithms, or replication protocols.
• Experience with Kubernetes or modern cloud infrastructure.
• Experience with virtualization, hypervisors, containers, or Firecracker.
• Kernel, operating-systems, or low-level runtime experience.
• Experience with concurrency, networking, or performance engineering.
• Contributions to systems-focused open-source projects.
• Published or ongoing systems research.
• Experience operating infrastructure used by real users.
• Familiarity with infrastructure for AI agents or long-running workloads.

Responsibilities

• Take ownership of tasks and write production-quality code.
• Investigate difficult problems.
• Explain your technical decisions.
• Contribute to distributed infrastructure for large-scale AI agent workloads.
• Work on persistent compute and distributed storage systems.
• Develop scheduling and orchestration platforms.
• Contribute to virtualization, containerization, and sandboxing infrastructure.
• Improve reliable multi-tenant cloud systems.
• Develop internal developer platforms and infrastructure tooling.
• Focus on performance, reliability, observability, and failure recovery.
• Work with production systems operating under real-world latency and fault-tolerance constraints.

Benefits

• Paid, full-time internship.
• Meals and office benefits included.
• Relocation support may be available.
• Visa support may be considered depending on the candidate and circumstances.
• Possible consideration for full-time employment, without any guarantee of conversion.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: No Education Listed