We're looking for a distributed systems engineer who will work across the stack to help build Archil volumes and solve customer problems as they arise. You’ll have significant influence over the technical and product direction.

What You'll Do:

• Build out never-before-seen capabilities in storage

• Design distributed systems interactions for atomicity and idempotency

• Deploy infrastructure and generalize infrastructure across different clouds

• Address issues in our production system as they arise to help our customers if anything goes wrong.

• Operate through changing customer requirements with lots of ambiguity

Who You Are:

• Deeply understand how computers work from the silicon up, and passionate about digging into systems, understanding them, building them, and fixing them

• A builder of databases and core infrastructure, not just a user

• Possess strong foundational knowledge of distributed systems, performance optimization, and low-level programming (e.g. C, C++, Golang, Rust, Haskell, OCaml)

• Thrive in a fast-paced, startup environment and are committed to customer success

Requirements:

• 2 - 10 years of experience building and operating distributed systems.
• Building cloud services (such as working on databases,storage systems),not just building applications that use those services
• Experience at startup or hyper-growth companies AND / OR top-tier large companies (ideal profile will have both)
• On-call experience for complex production issues

Education

Bachelor's degree in Computer Science or related field (bonus if from top-?tier school)

Hard skills

• Has worked professionally in a low-?level programming language (one of C,? C++, Rust, Golang, OCaml, Haskell)
• Deep understanding of how computers work from silicon up.
• Knowledge of distributed systems (consensus, scaling, API pitfalls).
• Debugging skills across multiple systems using metrics/logs.

Soft skills

Comfortable with ambiguity and changing requirements

Tech stack

Rust, C, Other Low-level Languages, Kernel drivers, Embedded systems, Spark Core, Ray Core, High-performance computing, Distributed systems