Technology Architect | Cloud Platform | Google Cloud - Architecture
Varite, Charlotte, NC, United States
Pay Rate Range: $71.42 - 73.52/hr.
Must Have Skills
Kubernetes (Production-grade clusters)
Google Kubernetes Engine (GKE)
Terraform (Infrastructure as Code)
Docker & Container Orchestration
CI/CD pipelines (Jenkins, GitOps, ArgoCD)
Python / Shell scripting
Cloud Platforms (GCP, AWS or Azure)
Linux Administration
Machine Learning platform enablement
MLOps / Model deployment pipelines
Helm Charts
Prometheus, Grafana, Dynatrace
ArgoCD, GitHub Actions
Kafka, Redis, Stateful workloads on Kubernetes
Job Description
We are seeking a highly skilled Kubernetes Engineer with strong experience in GKE, Terraform, and Cloud-Native Infrastructure, capable of supporting machine learning and high-scale enterprise workloads. The ideal candidate will have hands-on expertise in designing, building, and operating secure, scalable Kubernetes platforms, with exposure to ML model serving and MLOps pipelines.
This role requires close collaboration with application, ML, and DevOps teams to ensure reliable containerized deployments, automated infrastructure provisioning, and optimal platform performance.
Key Responsibilities
Design, deploy, and manage highly available Kubernetes clusters on GKE
Build and maintain Infrastructure as Code using Terraform
Support containerized analytics platforms on Kubernetes
Implement and manage CI/CD and GitOps pipelines (Jenkins, ArgoCD)
Containerize applications and ML workloads using Docker
Deploy and manage microservices, APIs, and batch jobs on Kubernetes
Implement monitoring, logging, and alerting using Prometheus, Grafana, Dynatrace
Manage Kubernetes networking, ingress, secrets, RBAC, autoscaling, and security
Optimize cluster performance, cost, and resource utilization
Troubleshoot production issues and support enterprise-grade SLAs
Collaborate with developers, data scientists, and platform teams
Required Skills & Qualifications
10+ years of overall IT experience with strong focus on DevOps / Cloud / Kubernetes
Extensive hands-on experience with Kubernetes (GKE preferred)
Strong experience with Terraform for cloud infrastructure provisioning
Hands-on experience with Docker, container orchestration, and microservices
Experience supporting ML workloads or data platforms on Kubernetes
Strong Linux administration and troubleshooting skills
CI/CD experience using Jenkins, Git, GitOps tools
Experience with cloud services on GCP (preferred), AWS, or Azure
Scripting experience with Python, Shell
Solid understanding of networking, security, and IAM concepts
Certifications (Required / Preferred)
Certified Kubernetes Administrator (CKA) - Preferred
Terraform Associate - Preferred
Cloud Certifications (GCP / AWS / Azure) - Preferred
Top 3 Responsibilities Expected from Subcon
Build and operate Kubernetes platforms with Terraform-based IaC
Enable and support open shift containers on Kubernetes
Ensure platform reliability through automation, monitoring, and DevOps best practices
Strong communication skills
Strong programming and automation skills
Interview Process - Face-to-face / In-person (Mandatory)
Work Location Requirement - Either Dallas or Charlotte client office
Client Office Addresses
Charlotte:, 300 S Brevard St, Charlotte, NC 28202
Must Have Skills
Kubernetes (Production-grade clusters)
Google Kubernetes Engine (GKE)
Terraform (Infrastructure as Code)
Docker & Container Orchestration
CI/CD pipelines (Jenkins, GitOps, ArgoCD)
Python / Shell scripting
Cloud Platforms (GCP, AWS or Azure)
Linux Administration
Machine Learning platform enablement
MLOps / Model deployment pipelines
Helm Charts
Prometheus, Grafana, Dynatrace
ArgoCD, GitHub Actions
Kafka, Redis, Stateful workloads on Kubernetes
Job Description
We are seeking a highly skilled Kubernetes Engineer with strong experience in GKE, Terraform, and Cloud-Native Infrastructure, capable of supporting machine learning and high-scale enterprise workloads. The ideal candidate will have hands-on expertise in designing, building, and operating secure, scalable Kubernetes platforms, with exposure to ML model serving and MLOps pipelines.
This role requires close collaboration with application, ML, and DevOps teams to ensure reliable containerized deployments, automated infrastructure provisioning, and optimal platform performance.
Key Responsibilities
Design, deploy, and manage highly available Kubernetes clusters on GKE
Build and maintain Infrastructure as Code using Terraform
Support containerized analytics platforms on Kubernetes
Implement and manage CI/CD and GitOps pipelines (Jenkins, ArgoCD)
Containerize applications and ML workloads using Docker
Deploy and manage microservices, APIs, and batch jobs on Kubernetes
Implement monitoring, logging, and alerting using Prometheus, Grafana, Dynatrace
Manage Kubernetes networking, ingress, secrets, RBAC, autoscaling, and security
Optimize cluster performance, cost, and resource utilization
Troubleshoot production issues and support enterprise-grade SLAs
Collaborate with developers, data scientists, and platform teams
Required Skills & Qualifications
10+ years of overall IT experience with strong focus on DevOps / Cloud / Kubernetes
Extensive hands-on experience with Kubernetes (GKE preferred)
Strong experience with Terraform for cloud infrastructure provisioning
Hands-on experience with Docker, container orchestration, and microservices
Experience supporting ML workloads or data platforms on Kubernetes
Strong Linux administration and troubleshooting skills
CI/CD experience using Jenkins, Git, GitOps tools
Experience with cloud services on GCP (preferred), AWS, or Azure
Scripting experience with Python, Shell
Solid understanding of networking, security, and IAM concepts
Certifications (Required / Preferred)
Certified Kubernetes Administrator (CKA) - Preferred
Terraform Associate - Preferred
Cloud Certifications (GCP / AWS / Azure) - Preferred
Top 3 Responsibilities Expected from Subcon
Build and operate Kubernetes platforms with Terraform-based IaC
Enable and support open shift containers on Kubernetes
Ensure platform reliability through automation, monitoring, and DevOps best practices
Strong communication skills
Strong programming and automation skills
Interview Process - Face-to-face / In-person (Mandatory)
Work Location Requirement - Either Dallas or Charlotte client office
Client Office Addresses
Charlotte:, 300 S Brevard St, Charlotte, NC 28202