AI Infrastructure Architect | Kubernetes & GPU Ops

Sapsf; United States; On-site; USD 140,000 - 170,000; Full time

Job summary

Sapsf seeks an experienced AI Factory Platform Operations Engineer to support deployment, operations, troubleshooting, and reliability of enterprise AI infrastructure. You will manage Linux-based infrastructure, Kubernetes, container platforms, networking, automation, and observability across AI/GPU environments.

Collaborate with infrastructure, network, DevOps, cloud, security, and engineering teams to maintain availability, perform root cause analysis, and improve operational reliability.

Qualifications

• Proficient Linux administration experience (RHEL/ Rocky/ Ubuntu).
• Kubernetes production experience including architecture, networking, storage, RBAC, upgrades.
• Docker/container runtime knowledge and troubleshooting skills.
• Strong networking fundamentals: TCP/IP, DNS, routing, load-balancing.
• Shell/Bash scripting and log analysis for operations.
• Experience with incident management and root cause analysis (RCA).
• Experience with infrastructure monitoring and observability tools.
• Version control with Git and collaboration workflows.
• Infrastructure-as-Code tooling (Ansible/Terraform) and cloud exposure.

Responsibilities

• AI/GPU infrastructure operations and support for enterprise platforms.
• Perform health checks and troubleshooting to ensure platform reliability.

Skills

Linux administration

Kubernetes administration

Docker/container runtime

Networking fundamentals

Scripting (Shell/Bash)

Performance analysis

Incident management/RCA

Git/version control

Infrastructure monitoring

Tools

Kubernetes

Docker

Prometheus

Grafana

Splunk

Datadog

Dynatrace

Ansible

Terraform

Job description

Sapsf seeks an experienced AI Factory Platform Operations Engineer to support deployment, operations, troubleshooting, and reliability of enterprise AI infrastructure. You will manage Linux-based infrastructure, Kubernetes, container platforms, networking, automation, and observability across AI/GPU environments.

Collaborate with infrastructure, network, DevOps, cloud, security, and engineering teams to maintain availability, perform root cause analysis, and improve operational reliability.