Site Reliability Engineer (US - Pacific time)

The role

This role focuses on making a fast-growing, data-heavy platform dependable through automation, rather than doing routine alert firefighting. The engineer works across a multi-account AWS setup and many Kubernetes-hosted services, dealing with scale problems that appear only at very large data volumes. The position is based in San Francisco and is aimed at candidates working on US Pacific hours.

What you would do

• Run Kubernetes clusters across several environments, covering autoscaling, networking, and GitOps-driven deployments.
• Grow and manage a multi-account AWS organization, including provisioning, network design, access policies, and links between accounts.
• Keep the Terraform and Terragrunt codebase healthy, including shared modules and pipelines that plan on pull requests and apply on merge.
• Improve internal tooling for releases, schema changes, backups, restores, and incident handling.
• Find recurring operational pain points and remove them through code and self-healing automation.
• Monitor and trim cloud spend as the platform expands.
• Take part in on-call rotations and incident response, aiming to lower incident frequency over time.
• Design automation for provisioning, scaling, rebalancing, and recovery of stateful systems.

What they asked for

• Hands-on production Kubernetes experience, ideally on EKS, including diagnosing node pressure, networking faults, and failed rollouts across thousands of nodes.
• Proven record running production AWS environments spread across many accounts, with a solid grasp of IAM, organizational boundaries, and cross-network connectivity.
• Practical experience codifying infrastructure in Terraform or Terragrunt for large environments, including how modules are structured and how state is managed.
• Working knowledge of Linux internals, covering storage, memory, networking, and common failure modes.
• Track record supporting stateful services such as databases, message queues, or storage systems.
• Ability to investigate performance and reliability problems in live systems.
• Willingness to own systems end to end, including on-call duties.

Nice to have

• Familiarity with GitOps tooling such as ArgoCD and CI/CD pipelines built on GitHub Actions.
• Experience building foundational infrastructure services that AI agents can use, for fast-moving teams.
• Exposure to multi-region architectures and the trade-offs between consistency and availability.