Senior Kubernetes / GCP Platform Engineer (GKE)
Location: Scottsdale, AZ (Hybrid)
Employment Type: Contract (W2 through ZipStaff — No C2C or 1099)
Duration: 12 months, with likely extension
About the Opportunity:
What You’ll Do:
- Design, operate, and support Kubernetes on GCP (GKE).
- Build and maintain IaC with Terraform, Helm, and GitHub Actions.
- Automate platform work with Python, Ansible, and Node.js.
- Run Prometheus and Grafana for production observability.
- Handle incident management, on-call, and production triage.
- Own CI/CD pipelines and platform automation.
- Apply AI/ML and AIOps practices (model lifecycle, monitoring, AI-driven alerting).
- Support Linux systems and network fundamentals on a large distributed / microservices footprint.
- 7+ years of platform, SRE, or cloud engineering experience.
- Strong Kubernetes and GCP (GKE).
- Strong Terraform, Helm, and GitHub Actions.
- Proficiency in Python, Ansible, and Node.js.
- Strong Prometheus and Grafana.
- Solid Linux and networking fundamentals.
- Incident management, on-call, and production triage.
- Hands-on CI/CD and automation.
- Working understanding of AI/ML concepts and AIOps (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.
- Google Cloud Architect.
- Certified Kubernetes Administrator (CKA).
- Java / J2EE / Spring Boot.
- MLOps or operating ML/AI platforms and pipelines.
- AIOps tools, anomaly detection, or predictive analytics.
- Large-scale distributed systems and microservices.
- GPU workloads or ML infrastructure on GCP.
- Kubeflow, Vertex AI, or ML pipelines.
- AI-driven automation in monitoring and incident response.
- Healthcare insurance (employee-only).
- Dental insurance.
- Vision insurance.
- 401(k).
- Paid time off.
Skills
- AI
- Analytics
- Anomaly Detection
- Ansible
- Automation
- CI/CD
- Cloud
- Distributed Systems
- GCP
- GitHub
- GitHub Actions
- GKE
- Grafana
- Helm
- Infrastructure as Code
- J2EE
- Java
- Kubeflow
- Kubernetes
- Linux
- Machine Learning
- Microservices
- MLOps
- Networking
- Node.js
- Observability
- Predictive Analytics
- Prometheus
- Python
- Spring
- Terraform
- Vertex AI