SYSTEMS ENGINEER @ 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 virtualization, distributed systems, storage, networking, orchestration, and low-level runtime infrastructure. Every millisecond, every sys-call, every scheduling decision matters.
We’re looking for systems engineers who enjoy understanding computers all the way down.
YOU MIGHT BE A FIT IF YOU
- Think abstractions are useful because you understand what’s underneath them.
- Care about latency, throughput, memory usage, and tail performance.
- Enjoy debugging problems that take days to understand and minutes to fix.
- Believe reliability is a feature.
- Think distributed systems are fun rather than frightening.
- Get excited reading kernel commits, infrastructure blogs, or systems papers.
- Have strong opinions about operating systems, virtualization, networking, or storage.
- Like making difficult systems feel simple.
- Measure before optimizing, then optimize relentlessly.
- View performance engineering as product engineering.
- Believe the best infrastructure disappears into the background.
- Are high agency and fiercely independent.
- Say how things ought to be built, then build them.
- Are a competitive teammate with a heart of gold.
- Are hungry to learn, improve, and reflect deeply on feedback.
- Go above and beyond in everything you do.
WHAT YOU’LL BUILD
- Distributed infrastructure for large-scale agent workloads.
- Virtualization and sandboxing systems.
- Persistent compute and storage primitives.
- Scheduling, orchestration, and reliability systems.
- Runtime infrastructure for long-running AI agents.
- Internal developer platforms and tooling.
- Production systems operating under real-world scale, latency, and reliability constraints.
REPRESENTATIVE PROJECTS
You might find yourself working on problems like:
- Building a distributed storage layer for persistent agent state.
- Improving sandbox startup latency from seconds to milliseconds.
- Designing scheduling systems that efficiently allocate compute across thousands of concurrent agents.
- Developing virtualization and isolation technologies for secure multi-tenant workloads.
- Profiling bottlenecks across networking, storage, scheduling, and runtime layers.
- Building developer infrastructure that makes deploying and operating AI agents dramatically simpler.
WHAT WE LOOK FOR
preferred
), Go, C/C++, or similar systems languages.
- Strong software engineering fundamentals.