Senior Site Reliability Engineer, AI Platforms
About The Position
Focused is seeking a Senior Site Reliability Engineer to embed with a fast-growing AI developer platform company. The engineer will help customers deploy and operate the platform on their own infrastructure, maintain its health at scale, and make upgrades reliable and predictable. The role is suited to someone experienced in operating stateful, self-hosted software in Kubernetes environments for demanding customers. The position includes operating and improving Kubernetes deployments and their backing services, defining reliability objectives, responding to incidents, automating operational work, and building infrastructure and CI/CD across major cloud providers. The role requires working directly with customers to troubleshoot varied environments, including private-networked, air-gapped, and regulated deployments. The position requires working in the Denver office three days per week and up to 20% travel within the United States. Focused is unable to sponsor or take over sponsorship of an employment visa at this time. The Denver base salary range is $160,000–$195,000.
Requirements
- At least 6 years in SRE, platform, or infrastructure engineering.
- Deep hands-on experience with Kubernetes and Helm in production.
- Experience with GitOps tooling such as ArgoCD or Flux.
- Experience operating stateful services in Kubernetes, such as Postgres, Redis, ClickHouse, Kafka, or similar.
- Proficiency with Terraform or similar infrastructure-as-code tools.
- Experience with at least one major cloud provider (AWS, GCP, or Azure) and its managed Kubernetes service.
- Solid scripting and automation skills using Python, Go, or Bash.
- Comfort working directly with customers to debug their environments.
Nice To Haves
- Experience supporting self-hosted or on-premises deployments of a commercial software product.
- Experience with air-gapped or regulated environments, such as FedRAMP, HIPAA, or SOC 2.
- Familiarity with observability tooling such as OpenTelemetry, Prometheus, Grafana, Datadog, or Honeycomb.
- Exposure to LLM applications, agent frameworks, or LLM observability and evaluation tools.
- Experience writing or maintaining Helm charts that other teams depend on.
- Experience scaling ClickHouse or another analytical database under heavy ingest.
- Contributions to open-source infrastructure or AI tooling.
- Strong technical writing, with runbooks that get used.
Responsibilities
- Deploy, upgrade, and operate a containerized AI platform in customer-owned Kubernetes environments using Helm and GitOps (ArgoCD).
- Own the health of stateful in-cluster backing services, including Postgres, Redis, and ClickHouse.
- Troubleshoot deployments across varied customer setups, including private networking, air-gapped, and regulated environments.
- Turn recurring customer issues into improved Helm charts, runbooks, and documentation.
- Define and track SLIs and SLOs for self-hosted deployments.
- Lead incident response and blameless post-mortems.
- Perform capacity planning and performance tuning for high-volume trace and event data.
- Reduce toil through automation.
- Build and maintain infrastructure with Terraform across AWS, GCP, and Azure, including EKS, GKE, and AKS.
- Build CI/CD pipelines that test upgrade paths and catch regressions before customers do.
- Apply security best practices, including secrets management, RBAC, network policy, and SSO.
- Work directly with customers to debug their environments.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
