Site Reliability Engineer — Dallas, TX

About The Role

The role owns the reliability of large-scale, distributed production systems — Kubernetes clusters, service meshes, and the CI/CD pipelines that ship code to them hundreds of times a day.

This is a hands-on SRE position on a team that treats uptime as an engineering problem: error budgets, SLOs, and automation over toil. The work directly protects revenue and user experience across systems handling millions of requests per minute.

Key Responsibilities

• Build, operate, and scale Kubernetes infrastructure (EKS/GKE) across multi-region environments, including cluster upgrades, autoscaling policies, and workload placement

• Define and enforce SLOs and error budgets with product teams, translating reliability targets into concrete engineering priorities

• Design observability from the ground up: metrics, logs, and traces using Prometheus, Grafana, and OpenTelemetry, with actionable alerting that pages humans only when it should

• Automate infrastructure provisioning with Terraform and GitOps workflows (ArgoCD or Flux), eliminating manual configuration and drift

• Lead blameless postmortems for production incidents, drive root-cause fixes, and reduce mean time to recovery through runbooks and tooling

• Improve CI/CD pipelines for safe, fast deploys — progressive rollouts, canary analysis, and automated rollback via Spinnaker or Argo Rollouts

• Capacity plan and performance-tune core infrastructure: databases, message queues (Kafka), and load balancers under real production traffic

What We Are Looking For

• 3–7 years of experience in SRE, DevOps, or backend infrastructure engineering, including on-call ownership of production systems at scale

• Deep hands-on expertise with Kubernetes in production — operating clusters, debugging workloads, and writing custom operators or controllers is a plus

• Strong infrastructure-as-code skills with Terraform; comfort with AWS or GCP core services (compute, networking, IAM, storage)

• Proficiency in Go, Python, or Bash for building internal tooling, automation, and observability integrations

• Solid understanding of distributed systems failure modes: consensus, retries, backpressure, cascading failures, and tail latency

• Experience running incident response and postmortem processes; strong written communication under pressure

• Bonus: experience with service mesh (Istio/Linkerd), chaos engineering practices, eBPF-based observability, or multi-cloud architectures; BS/MS in Computer Science or equivalent practical experience