Kubernetes / GCP Engineer

Codetech • Scottsdale, AZ

13h • Hybrid

About The Position

The Kubernetes / GCP Engineer will support Kubernetes and Google Cloud Platform (GKE) environments, infrastructure as code, automation, CI/CD, observability, and production operations. The role also calls for knowledge of AI/ML concepts and AIOps practices, including model lifecycle, monitoring, and AI-driven alerting. The position is a one-year contract that is expected to be renewed. Scottsdale, Arizona, hybrid work is preferred; remote work is also listed.

Requirements

• Strong experience with Kubernetes and GCP (GKE).
• Strong experience with infrastructure as code (Terraform), Helm, and GitHub Actions.
• Proficiency in Python, Ansible, and Node.js.
• Strong experience with the Prometheus and Grafana observability stack.
• Solid understanding of 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, including model lifecycle, monitoring, or AI-driven alerting.

Nice To Haves

• Google Cloud Architect Certification.
• Certified Kubernetes Administrator (CKA).
• Experience in Java/J2EE and Spring Boot.
• Experience supporting or operating ML/AI platforms or pipelines (MLOps).
• Exposure to AIOps tools, anomaly detection, or predictive analytics systems.
• Experience with large-scale distributed systems and microservices architecture.
• 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.

Responsibilities

• Support Kubernetes and GCP (GKE) environments.
• Build and maintain infrastructure as code using Terraform, and work with Helm and GitHub Actions.
• Develop automation and CI/CD pipelines.
• Use Prometheus and Grafana for observability.
• Participate in incident management, on-call support, and production triage.
• Apply AI/ML and AIOps practices, such as model lifecycle support, monitoring, and AI-driven alerting.

What This Job Offers

• Education Level: No Education Listed