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KubernetesGCP Engineer
Job Location:
Job Location:
Scottsdale, AZ - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
3 September 2026 (11 hours ago)
Posted:
Application Deadline:
1 December 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Job Description
Location: Scottsdale AZ (Hybrid)
Length of contract : 1 year (and will be renewed after that)
We have a requirement for a Kubernetes/GCP resource with the following skillsets.
Required Qualifications
Strong experience with Kubernetes and GCP (GKE)
Strong experience in IaC (Terraform) Helm and GitHub Actions
Proficiency in Python Ansible
Strong experience with 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 (model lifecycle monitoring or AI-driven alerting)
Preferred Qualifications
Google Cloud Architect Certification
Certified Kubernetes Administrator (CKA)
Experience in Java/J2EE 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
Location: Scottsdale AZ (Hybrid)
Length of contract : 1 year (and will be renewed after that)
We have a requirement for a Kubernetes/GCP resource with the following skillsets.
Required Qualifications
Strong experience with Kubernetes and GCP (GKE)
Strong experience in IaC (Terraform) Helm and GitHub Actions
Proficiency in Python Ansible
Strong experience with 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 (model lifecycle monitoring or AI-driven alerting)
Preferred Qualifications
Google Cloud Architect Certification
Certified Kubernetes Administrator (CKA)
Experience in Java/J2EE 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
Required Skills:
