Required Qualifications
Strong experience with Kubernetes and GCP (GKE)
Strong experience in IaC (Terraform), Helm, and GitHub Actions
Proficiency in Python, Ansible, Node.js
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

GKE/GCP Cloud Data Engineer

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