Distributed systems at scale: You have proven success designing, scaling, and hardening distributed systems, all while keeping them reliable under high-load production environments
A performance-driven mindset: You have practical experience profiling, benchmarking, and optimizing distributed systems, with sound judgment about latency, throughput, caching, and resource tradeoffs
Thrive in ambiguity: You thrive on transforming ambiguous performance problems into measured action and durable fixes. You work ahead of demand, identifying constraints before they reach customers
A track record of ownership: You've led complex projects from design through deployment, carried them in production, and made difficult calls under visible risk and conflicting requirements
A customer-centric mindset: You keep the customers top of mind, and you can translate their needs into actionable changes in the codebase
Technical & infrastructure proficiency: You have strong fundamentals in microservices and cloud-native infrastructure technologies (Docker, Kubernetes, Terraform) alongside languages like Go, Rust, Java, or C++
Collaboration and communication: You are comfortable working across functions to align on priorities and to explain technical tradeoffs clearly to technical and non-technical partners alike
Mentorship: You have an interest in growing other engineers, such as mentoring teammates on the team's systems, helping newer engineers find their footing, or contributing to how we hire
Experience: You have 5 - 8 years of professional software development experience, including time spent building and operating distributed systems but we care more about what you've built than the exact number
We know great engineers come from many different paths. If you're excited about this work but don't match every point below, we'd still love to hear from you. What you've built and how you think matters more to us than a perfect checklist
Familiarity with the OCI image and distribution specs
Experience building container registry products
Experience with storage or caching systems at scale