Senior Site Reliability Engineer, AI Platforms
About The Position
Focused is hiring a Senior Site Reliability Engineer to embed with a fast-growing AI developer platform company. The role helps customers run the platform on their own infrastructure by deploying it, maintaining its health at scale, and making upgrades reliable and routine. It is suited to an engineer experienced with stateful, self-hosted software in Kubernetes environments serving demanding customers. The position involves operating a containerized AI platform in customer-owned Kubernetes environments and supporting varied deployments, including private-networked, air-gapped, and regulated environments. The engineer will improve reliability through service-level objectives, incident response, capacity planning, performance tuning, and automation, while building and maintaining cloud infrastructure and deployment pipelines.
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 in 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 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 and experience producing useful runbooks.
Responsibilities
- Deploy, upgrade, and operate a containerized AI platform in customer-owned Kubernetes environments using Helm and GitOps tooling such as 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 encounter them.
- Apply security best practices, including secrets management, RBAC, network policy, and SSO.
- Work directly with customers to debug their environments.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
