GKE Engineer

MACHINE LEARNING TECHNOLOGIES LLC; Phoenix (AZ); On-site; USD 120,000 - 180,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC in Phoenix, AZ is seeking a GKE Engineer to design, deploy and manage Google Kubernetes Engine clusters, ensuring scalable, secure and reliable cloud-native operations.

You will drive automation with Terraform, build CI/CD pipelines, and implement security and observability practices. This role collaborates with SRE, security, and development teams to deliver resilient cloud platforms. The engagement is ongoing with strong growth potential.

Qualifications

• 4+ years of DevOps or cloud platform engineering experience.
• Hands-on with Google Cloud Platform (GCP) and GKE.
• Strong knowledge of Kubernetes components and security.

Responsibilities

• Design, deploy, and manage Kubernetes clusters on GKE.
• Configure node pools, autoscaling, networking, load balancing, and upgrades.
• Deploy applications using Kubernetes manifests, Helm, and Kustomize.
• Implement CI/CD pipelines for automated builds, testing, deployment, and release management.
• Automate infrastructure provisioning with Terraform and IaC practices.
• Apply Kubernetes security best practices (RBAC, Workload Identity, secrets management).
• Configure monitoring, logging, alerting, and observability with Prometheus, Grafana, and Google Cloud Operations.
• Troubleshoot cluster, networking, deployment, performance, and availability issues.
• Collaborate with development, SRE, security, and platform teams for cloud-native modernization.

Skills

DevOps experience

GCP & GKE

Kubernetes architecture

Docker

Terraform

CI/CD pipelines

Linux networking

Scripting

Tools

Jenkins

GitHub Actions

GitLab CI

Cloud Build

Prometheus

Grafana

Job description

Job Overview

• Job ID: J53355
• Job Title: GKE Engineer
• Location: Pheonix, AZ
• Duration: 12 Months + Extension
• Domain Exposure: Pharmaceuticals
• Work Authorization: US Citizen,Green Card,OPT-EAD,CPT,H-1B,H4-EAD,L2-EAD,GC-EAD
• Client: To Be Discussed Later
• Employment Type: W-2, 1099, C2C

Key Responsibilities

• Design, deploy, and manage Kubernetes clusters and containerized workloads using Google Kubernetes Engine (GKE).
• Configure and maintain GKE clusters, including node pools, autoscaling, networking, load balancing, and cluster upgrades.
• Deploy and manage applications using Kubernetes manifests, Helm charts, and Kustomize.
• Implement CI/CD pipelines for automated application builds, testing, deployment, and release management.
• Automate infrastructure provisioning and configuration using Terraform and Infrastructure as Code (IaC) practices.
• Implement Kubernetes security best practices, including RBAC, Workload Identity, secrets management, network policies, and container image security.
• Configure monitoring, logging, alerting, and observability using Google Cloud Operations Suite, Prometheus, and Grafana.
• Troubleshoot cluster, networking, application deployment, performance, and production availability issues.
• Optimize cluster resource utilization, scalability, reliability, and cloud infrastructure costs.
• Collaborate with application development, SRE, security, and platform engineering teams to support cloud-native modernization.

Required Skills and Qualifications

• 4+ years of experience in DevOps, cloud infrastructure, platform engineering, or Kubernetes administration.
• Hands-on experience with Google Cloud Platform (GCP) and Google Kubernetes Engine (GKE).
• Strong understanding of Kubernetes architecture, including Pods, Deployments, Services, Ingress, ConfigMaps, Secrets, StatefulSets, and persistent storage.
• Experience with Docker or other OCI-compliant container technologies.
• Proficiency in Terraform or similar Infrastructure as Code tools.
• Experience developing and maintaining CI/CD pipelines using tools such as Cloud Build, Jenkins, GitHub Actions, or GitLab CI.
• Knowledge of Linux administration, networking, DNS, TLS, load balancing, and troubleshooting.
• Experience with monitoring, logging, and alerting tools.
• Familiarity with Git-based workflows, scripting, and automation using Python, Bash, or Go.

Success Criteria

• Reliable, secure, and scalable GKE platform operations.
• Reduced deployment lead time through CI/CD and automation.
• Improved service availability and faster incident resolution.
• Optimized cloud resource utilization and infrastructure costs.
• Consistent adherence to security, compliance, and operational standards.

Equal Opportunity Employer

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.