Build and own core compute infrastructure for Render's cloud platform, including Kubernetes clusters on hyperscalers and bare metal. Design, scale, debug, and optimize large-scale orchestration, scheduling, and distributed systems with deep Kubernetes and systems expertise.
170k – 290k
Remote7+ YOEDevOps / SRE
About the role
What You'll Do
Own Render's core compute infrastructure across multiple cloud providers, regions, and data centers. Shape how the compute platform evolves as the company rapidly scales.
Design and build capabilities that give users greater performance and flexibility in how their services are built, deployed, perform, and stay available even when underlying resources go down.
Investigate challenging cloud and compute issues across the stack, from the kernel and data plane to the Kubernetes cluster, control plane, and other orchestration mechanisms.
Improve the performance and reliability of the infrastructure through systematic profiling, experimentation, and tuning.
Partner with engineers across the company to build a platform that is stable, predictable, and secure.
Participate in the on-call rotation. Help continuously improve how incidents are detected, responded to, and learned from.
What We're Looking For
At least 7 years of experience building and operating large-scale platform or compute infrastructure.
Deep expertise in operating, scaling, and enhancing Kubernetes clusters or similar resource/container orchestration systems.
Experience developing in Go, Rust, or similar languages to develop custom infrastructure components, scheduling, controllers that apply business logic to resource management.
Comfort going broad and deep in complex systems, making tradeoffs to improve performance and efficiency without sacrificing reliability.
Strong experience designing, debugging, and operating distributed systems.
Experience planning and executing rapid, high-risk upgrades and changes with minimal downtime to user services.
Nice-to-Haves
Background in virtualization technologies like Firecracker, gVisor, Kata, or similar.
Experience optimizing the performance of node, pod, and container spin-up times.
Familiarity with eBPF, Linux kernel internals, resource management.
Comfort securing and isolating workloads in multi-tenant execution environments.
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