Cloud Engineer/Site Reliability Architect

About the role

This is a Kubernetes-heavy platform engineering role supporting large-scale, multi-cloud GPU infrastructure. Success requires deep operational judgment, disciplined debugging, strong automation skills, and the ability to protect platform stability while capacity grows rapidly.

Responsibilities

• Operate Kubernetes platforms at significant scale across providers, including Amazon Elastic Kubernetes Service (EKS), CoreWeave Kubernetes Service (CKS), and Google Kubernetes Engine (GKE).
• Own the Kubernetes cluster lifecycle, including node-pool design and management, scheduler troubleshooting, container network interface (CNI) and network-policy troubleshooting, capacity planning, and safe rolling upgrades across large fleets.
• Develop, review, and maintain infrastructure as code with Terraform, along with Python tooling and automation that improve reliability, repeatability, and operational efficiency.
• Define and maintain service-level indicators (SLIs) and service-level objectives (SLOs); build monitoring and alerting that surface meaningful risks before they affect workloads.
• Debug complex distributed-system failures by forming hypotheses, testing them methodically, and separating temporal correlation from causation.
• Provision high-performance computing (HPC) and GPU infrastructure through the Conveyor CI/CD system across AWS, CoreWeave, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI), with additional providers as the platform expands.
• Coordinate daily with Networking, Storage, Security, and AI/ML platform teams to resolve cross-system dependencies and improve the end-to-end developer and researcher experience.
• Bring forward well-reasoned proposals, solutions, and informed opinions; use available tools and resources to self-unblock and drive issues to resolution.

Requirements

• Hands-on Kubernetes experience including node pool sizing