Kubernetes / GCP Engineer

Job Title:

Kubernetes / GCP Engineer

Location:

Scottsdale, AZ (Hybrid)

Employment Type:

Contract (W2 through ZipStaff)

About the Opportunity:

ZipStaff is seeking a Kubernetes / GCP Engineer to support cloud-native platform operations for a major healthcare organization in Scottsdale, AZ.

This hybrid role focuses on GKE, infrastructure-as-code, observability, production support, and applying AIOps practices to improve monitoring and incident response. The initial assignment is approximately one year, with potential extension.

What You'll Do:

• Administer and support Kubernetes platforms on GCP / GKE .
• Build and maintain infrastructure as code using Terraform , Helm , and GitHub Actions .
• Develop automation using Python, Ansible, and Node.js .
• Implement and operate observability with Prometheus and Grafana .
• Support incident management, on-call, and production triage.
• Build and improve CI/CD pipelines and operational automation.
• Apply AI/ML concepts and AIOps practices (model lifecycle, monitoring, or AI-driven alerting) to platform operations.
• Troubleshoot Linux systems, networking, and production platform issues.

Required Qualifications:

• Strong hands-on experience with Kubernetes and GCP (GKE) .
• Strong experience with Terraform, Helm, and GitHub Actions .
• Proficiency in Python, Ansible, and Node.js .
• Strong experience with the Prometheus and Grafana observability stack.
• Solid Linux systems and networking fundamentals.
• Experience in incident management, on-call support, and production triage.
• Hands-on experience with automation and CI/CD pipelines.
• Strong understanding of AI/ML concepts and AIOps practices (model lifecycle, monitoring, or AI-driven alerting).
• Ability to work hybrid in Scottsdale, AZ .
• Must be legally authorized to work in the United States without sponsorship now or in the future.

Preferred Qualifications:

• Google Cloud Architect Certification.
• Certified Kubernetes Administrator (CKA).
• Experience with Java / J2EE / Spring Boot.
• Experience supporting or operating ML/AI platforms or pipelines (MLOps).
• Exposure to AIOps tools, anomaly detection, or predictive analytics.
• Experience with large-scale distributed systems and microservices.
• Experience with GPU-based workloads or ML infrastructure on GCP.
• Knowledge of Kubeflow, Vertex AI, or ML pipelines.
• Experience integrating AI-driven automation into monitoring and incident response.

About ZipStaff:

ZipStaff partners with leading organizations to connect skilled technology professionals with high-impact contract opportunities. We focus on quality matches and long-term success.