Rust Engineer

yeet is built by a tight-knit group of systems, observability, and kernel nerds who refuse to accept “mystery outages” as normal. We’re a small, high-impact team with domain expertise in Linux, eBPF, performance instrumentation, and developer tooling.

We move fast, ship often, and take deep ownership. If you enjoy operating close to the metal, building tools that real engineers lean on during 3 AM incident sprints, and solving hard problems with minimal overhead, you’ll feel right at home here.

We’re looking for a Rust engineer to join us in building yeetd, our dynamic BPF runtime that powers on-demand observability across fleets of Linux servers.

You’ll be living close to the kernel, pushing Rust’s concurrency model to its limits, and solving problems that don’t have StackOverflow answers and make even ChatGPT throw its hands up in the air and say “idk.”

• You have deep systems-level experience with Linux, the kind that comes from debugging cryptic kernel errors at 2 AM and knowing which mailing list thread to dig up or which snippets of code in the kernel’s source tree to dig into.

• You’re fluent in Rust beyond syntax, you know how to work with the borrow checker to design safe, concurrent systems instead of fighting it.

• You understand synchronization primitives, memory models, and performance trade-offs, and you’re comfortable reasoning about them under real-world load.

• You’ve worked with (or are excited to dive into) eBPF, perf events, and kernel instrumentation, and you get a kick out of making low-level data both safe and usable.

• You’re the kind of engineer who enjoys turning “black box” Linux behavior into something observable and explainable.

• A degree in Computer Science, Electrical Engineering, or a related field with a focus on systems or networking.

• Hands-on experience with the Linux kernel contributing patches, debugging kernel modules, or building tools that live in kernel space.

• Familiarity with low-level networking (sockets, TCP/IP stack internals, packet processing).

• Prior work on extremely high-performance system software (databases, runtimes, observability tooling, compilers, etc.).

• Exposure to distributed systems or large-scale infrastructure, where performance and reliability trade-offs really matter.