Quick overview
Job description
About the Role
Join an AI infrastructure team and own end-to-end deployments into enterprise customer environments, from cloud VPCs to on-premises infrastructure. You will partner directly with customer IT, security, and platform teams to make complex deployments reliable and repeatable.
What You'll Do
Plan, configure, test, and roll out deployments across customer VPC and on-premises environments.
Work directly with customer engineering and leadership teams, including through shared channels and occasional on-site visits.
Diagnose and resolve customer-specific infrastructure issues involving Kubernetes configuration, cloud IAM, and networking.
Build monitoring, telemetry, and automation that turn one-off deployment work into reusable patterns.
Understand the hardware used for machine learning workloads and deploy models on customer-controlled infrastructure.
What We're Looking For
At least 3 years of experience in infrastructure engineering, DevOps, or SRE.
Deep production expertise with Kubernetes and Terraform, plus hands-on experience with AWS, GCP, or Azure.
Knowledge of networking, infrastructure as code, Docker, Linux, and cloud IAM.
Experience deploying software into customer-controlled environments, such as VPC, air-gapped, on-premises, or customer-managed Kubernetes environments.
Ability to communicate clearly and troubleshoot issues live with external engineering teams.
Experience with GPU infrastructure and tools such as Helm or Replicated/KOTS is relevant.
Compensation & Benefits
Base salary: $200,000 to $300,000 annually. Visa sponsorship is available.
Location
On-site in San Francisco, California, United States.
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