Staff Site Reliability Engineer

Doghouse Recruitment — Unknown · Posted ~1 week ago

Full-time Remote Visa History ✓

Skills

Linux Kubernetes Networking Terraform Docker CI/CD Go Python Production engineering Infrastructure reliability Helm TCP/IP DNS TLS

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Summary

A staff-level reliability engineering role focused on operating large-scale physical infrastructure, improving system performance, reducing operational toil, and building reliable automation for complex computing environments.

Highlights

Fully remote opportunity focused on large-scale infrastructure reliability, automation, performance optimization, and solving complex production challenges.

Description

Staff Site Reliability Engineer – Bare Metal Linux – Data Center – Networking Location: 100% remote within the EU Our client is building a cloud platform for high-throughput, compute-heavy workloads. They operate large-scale infrastructure where failure modes are real, capacity is finite, and reliability needs to be engineered, not "handled". We're seeking a Staff level SRE who will own production reliability end-to-end for our client: define SLIs/SLOs, run error budget conversations, and ship changes that reduce incidents and improve latency (p95/p99). You'll build automation to kill toil, improve deployment safety (canary/rollback), and turn observability into signal rather than noise. This is a bare-metal environment: think Linux, datacenters, physical fleets, and real hardware constraints, not managed services. You'll work close to the metal across Kubernetes internals (scheduling, autoscaling behavior, kubelet pressure/evictions, etcd/control plane), Linux performance (CPU/memory/IO contention), and network debugging (DNS/TCP/TLS, packet loss, congestion). On-call is part of the job, but success is measured by how much you reduce it. Requirements: • Production Engineering experience running / on-prem / data center infrastructure (not public cloud only) • Deep hands-on expertise in Linux systems debugging and performance (CPU, memory, IO, -level behaviors) • Strong understanding of networking (DNS/TCP/TLS, latency, packet loss, congestion, troubleshooting under load) • Strong Kubernetes experience beyond manifests: scheduler behavior, autoscaling edge cases, kubelet pressure/evictions, etcd/control plane • Experience with Terraform, Docker, Helm, and modern CI/CD practices • Strong recent coding skills in Go, and/or Python is a must for this role • Experience in Low Latency environments. If you're looking for complexity and a new place to nerd out on infrastructure optimization, we'd love to hear from you!