Senior Site Reliability Engineer, AI Platforms

Focused • Chicago, IL

4d • $165,000 - $200,000 • Hybrid

About The Position

Focused is hiring a Senior Site Reliability Engineer to embed with a fast-growing AI developer platform company. The role supports customers running the platform on their own infrastructure, including deployment, reliable operation at scale, and upgrades. It is suited to an engineer experienced in operating stateful, self-hosted software in Kubernetes environments for demanding customers, with an interest in agentic AI.

The position covers self-hosted platform reliability, site reliability engineering, and infrastructure across major cloud providers. The engineer will work directly with customers to troubleshoot deployments across varied environments, including private networking, air-gapped, and regulated setups. The role requires being in the Chicago office three days per week and up to 20% travel within the United States. Focused is unable to sponsor or take over sponsorship of employment visas at this time. The Chicago base salary range is $165,000–$200,000.

Requirements

• At least 6 years of experience 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, or Kafka.
• 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, including FedRAMP, HIPAA, or SOC 2.
• Familiarity with observability tools 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 used by other teams.
• Experience scaling ClickHouse or another analytical database under heavy ingest.
• Contributions to open-source infrastructure or AI tooling.
• Strong technical writing skills, including writing runbooks that are used.

Responsibilities

• Deploy, upgrade, and operate a containerized AI platform in customer-owned Kubernetes environments using Helm and GitOps tools such as ArgoCD.
• Own the health of stateful in-cluster backing services, including Postgres, Redis, and ClickHouse.
• Troubleshoot deployments across customer environments, including private networking, air-gapped, and regulated environments.
• Convert recurring customer issues into improvements to 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 operational 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 encounter them.
• Apply security best practices, including secrets management, RBAC, network policy, and SSO.
• Work directly with customers to debug their environments.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed