Distributed Systems Engineer
Location
New York
Posted
27 days ago
Salary
$125K - $250K / year
Job Description
Job Requirements
- You are fluent in Rust, C++, or a similarly performant backend language. We work primarily in Rust.
- You have experience deploying and monitoring high uptime applications to production in the cloud using orchestration and containerization (Docker, Terraform, Kubernetes).
- You have experience working within a large production codebase.
- You are extremely detail oriented and have a security mindset.
- You’re a clear communicator and value collaboration.
- You have a bias towards action and extremely strong work ethic.
- Bonuses
- You have experience working with blockchain nodes like Geth, Reth, or similar.
- You have experience with low-level details of Ethereum.
- You have experience working in an adversarial or security critical environment.
- Why work with us
- You’ll be working on groundbreaking tech that has the potential to be a key piece of infrastructure for the crypto industry
Related Guides
Related Categories
Related Job Pages
More Blockchain Engineer Jobs
Distributed Systems Engineer 5 – Membership Engineering
NetflixWhere you come to do the best work of your life. Follow @WeAreNetflix on Twitter, IG, Facebook, & Youtube for more
Distributed Systems Engineer developing commerce platform infrastructure at Netflix
Senior Compliance Manager, Blockchain & Crypto
N3XT SPORTSN3XT Sports is a sports consulting firm that specializes in digital transformation, innovation and investment strategy.
Senior Compliance Manager overseeing compliance framework for blockchain and crypto
Blockchain Partner Manager, Ecosystems
CircleCircle helps businesses and developers harness the power of stablecoins for payments and internet commerce worldwide.
Blockchain Partner Manager driving relationship management for Circle's blockchain partners
Distributed Training Engineer
Periodic LabsWe're building AI scientists and the autonomous laboratories for them to operate.
Optimize and develop large-scale distributed LLM training systems, support reinforcement learning workflows, and contribute to open-source frameworks.