GKE Engineer

Machine Learning Technologies, LLC; Phoenix (AZ); On-site; USD 120,000 - 150,000; Full time

Job summary

Machine Learning Technologies, LLC in Phoenix, AZ, seeks a seasoned DevOps engineer to design, deploy, and manage a GKE-based platform on Google Cloud. You will implement IaC with Terraform, build CI/CD pipelines, and enforce security, monitoring, and reliability across production workloads.

Join a cross-functional team to optimize resource use, automate operations, and advance cloud-native modernization with Kubernetes, Helm, and GitOps practices in a fast-paced environment.

Qualifications

• 4+ years of experience in DevOps, cloud infra, platform engineering, or Kubernetes administration.
• Hands-on with GCP and GKE.
• Strong Kubernetes architecture knowledge (Pods, Deployments, Services, Ingress, StatefulSets, storage).
• Experience with Docker or OCI containers.
• Proficiency with Terraform or similar IaC tools.
• Experience building CI/CD pipelines (Cloud Build, Jenkins, GitHub Actions, or GitLab CI).
• Linux admin, networking, DNS, TLS, load balancing, troubleshooting.
• Experience with monitoring and logging tools.
• Scripting with Python, Bash, or Go.

Responsibilities

• Design, deploy, and manage Kubernetes clusters and containerized workloads on GKE.
• Configure clusters: node pools, autoscaling, networking, load balancing, upgrades.
• Manage apps with Kubernetes manifests, Helm, and Kustomize.
• Implement CI/CD pipelines for automated builds, tests, deployments, releases.
• Automate infrastructure with Terraform and IaC practices.
• Apply Kubernetes security best practices (RBAC, Workload Identity, secrets).
• Configure monitoring, logging, alerting with Cloud Operations, Prometheus, Grafana.
• Troubleshoot cluster, networking, deployment, performance, availability.
• Optimize resource usage, scalability, reliability, costs.
• Collaborate with development, SRE, security, and platform teams for modernization.

Skills

Kubernetes architecture

Cloud infrastructure

Automation / scripting

Networking / DNS / TLS

Observability / monitoring

Tools

GKE

Docker

Terraform

CI/CD tools (Cloud Build, Jenkins, GitHub Actions, GitLab CI)

Prometheus / Grafana

Job description

• 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.

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.