Live opening · Posted 23 hours ago

Staff Site Reliability Engineer

Doghouse Recruitment · United States (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 23 hours ago
CompanyDoghouse Recruitment
LocationUnited States (Remote)
Salary$180K/yr - $250K/yr + Bonus, Stock · 5 benefits
Work modeYes
SkillsPython, Docker, Kubernetes, Terraform
SourceLinkedin
ListedPosted 23 hours ago

About the role

Description supplied by the original job listing.

Staff Site Reliability Engineer – Bare Metal Linux – Data Center – Networking
Location: 100% remote – US
Compensation: up to $350k OTE
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 networking: DNS/TCP/TLS, latency, packet loss, congestion, troubleshooting under load
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/InfiniBand, HFT or GPU cluster networking
Nice to have
Kubernetes internals on bare metal: scheduler behavior, autoscaling edge cases, kubelet pressure/evictions, etcd/control plane
InfiniBand
C development
Terraform, Puppet or Ansible; Docker, Helm and modern CI/CD
Why join
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!

Work arrangement
Yes

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