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Site Reliability Engineer

Job in Phoenix, Maricopa County, Arizona, 85001, USA
Listing for: Doghouse Recruitment
Full Time position Listed on 2026-11-15
Job specializations:
Salary/Wage Range or Industry Benchmark: 350000 USD Yearly USD 350000.00 YEAR

Job Description & How to Apply Below

Position: Staff Site Reliability Engineer

Staff Site Reliability Engineer – Bare Metal Linux – Data Center – Networking

Location: 100% remote – US

Compensation: up to $350k TC

Our client, a publicly listed AI cloud provider, is building a platform for high-throughput, compute-heavy workloads. They run 1,000+ bare-metal servers across their own datacenters, where failure modes are real, capacity is finite, and reliability needs to be engineered, not “handled”.

We’re looking for a Senior/Staff SRE to own production reliability end to end. You’ll 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, make deployments safer (canary/rollback), and turn observability into signal rather than noise.

This is a bare-metal environment:
Linux, datacenters, physical fleets and real hardware constraints, not managed services. You’ll work close to the metal across Linux performance (CPU/memory/I/O contention), network debugging (DNS/TCP/TLS, packet loss, congestion) and Kubernetes running on bare metal. On-call is part of the job, but success is measured by how much you reduce it.

Must-haves
  • Extensive, recent production experience running bare-metal / on-prem / datacenter infrastructure (not public cloud only), typically 15+ years in Linux-heavy roles
  • Experience operating large fleets of physical servers, directly or as part of a team
  • Deep hands-on Linux debugging and performance work at kernel level (CPU, memory, I/O, low-level behavior)
  • Strong coding in Go and/or Python
    , beyond automation scripts. Real engineering capability is a must.
  • Experience in low-latency environments
    , e.g. kernel tuning, CPU pinning/NUMA, kernel bypass, RDMA/Infini Band, HFT or GPU cluster networking
Nice to have
  • Kubernetes internals on bare metal: scheduler behavior, autoscaling edge cases, kubelet pressure/evictions, etcd/control plane
  • Infini Band
  • Terraform, Puppet or Ansible;
    Docker, Helm and modern CI/CD
  • Work on large-scale infrastructure powering the AI economy
  • 100% remote, with competitive compensation

If you’re looking for complexity and a new place to nerd out on infrastructure optimization, we’d love to hear from you!

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