Infrastructure Engineer Intern @ Dedalus Labs

Job description

# Infrastructure Engineer Intern **@ Dedalus Labs** ## Mission 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. ## About the internship 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. ## You might be a fit if you - Think distributed systems are one of computer science’s most beautiful subjects. - Want to understand why systems fail—not merely how to make the happy path work. - Have built something technically difficult relative to your experience. - Can explain the hardest part of a project, what failed, and what you personally contributed. - Care about consistency, fault tolerance, concurrency, latency, and system correctness. - Enjoy learning how operating systems, storage engines, schedulers, networks, and runtimes work. - Read technical papers, source code, or engineering postmortems because you are genuinely curious. - Prefer building and experimenting over collecting credentials. - Learn unusually quickly and act deeply on feedback. - Are comfortable working through ambiguity and taking ownership without waiting for detailed instructions. - Believe simple systems are often harder to build than complicated ones. - Measure before optimizing, then optimize relentlessly. - Are high agency and fiercely independent. - Are a competitive teammate with a heart of gold. - Go above and beyond in everything you do. ## What you’ll work on Depending on your strengths and the company’s needs, you may contribute to: - Distributed infrastructure for large-scale AI agent workloads. - Persistent compute and distributed storage systems. - Scheduling and orchestration platforms. - Virtualization, containerization, and sandboxing infrastructure. - Reliable multi-tenant cloud systems. - Internal developer platforms and infrastructure tooling. - Performance, reliability, observability, and failure recovery. - Production systems operating under real-world latency and fault-tolerance constraints. ## Representative projects You might find yourself working on problems like: - Building a component of a distributed storage system for persistent agent state. - Improving the reliability or recovery behavior of a production service. - Designing scheduling infrastructure for concurrent, long-running agent workloads. - Investigating a bottleneck across storage, networking, scheduling, or runtime layers. - Building internal tooling that makes infrastructure easier to operate and debug. - Designing tests that simulate partial failures, machine loss, or degraded networks. - Improving observability for distributed workloads. - Prototyping a new isolation, caching, or orchestration mechanism. - Reading a systems paper, implementing part of it, and comparing its tradeoffs with our architecture. Your project will be scoped to the internship, but it should matter to the company and be used by real engineers or systems. ## What we look for - 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. We evaluate candidates relative to their experience and opportunities. You do not need a prestigious employer, advanced degree, or long résumé. Students, recent graduates, researchers, self-taught engineers, open-source contributors, and early-career engineers are all welcome to apply. What matters is the difficulty and quality of what you have done, what you personally owned, and how quickly you are improving. ## Especially strong signals - Self-directed systems projects built beyond required coursework. - Meaningful open-source contributions. - A storage engine, scheduler, database, runtime, compiler, operating system, hypervisor, container system, or distributed service you built. - A correct implementation of Raft, Paxos, replication, sharding, or another distributed-systems concept—with thoughtful testing and documentation. - Technical writing that explains architecture, failure modes, and tradeoffs. - Evidence that other people use or depend on something you built. - Research accompanied by a working implementation. - A project where you encountered a difficult failure and can explain how you diagnosed it. - Repeated evidence of unusually fast learning and end-to-end ownership. Class projects can demonstrate baseline knowledge. Projects that you initiated, substantially extended, or pursued beyond their requirements are generally strong