GeorgiaTEK Systems Inc. · 6 hours ago
Platform Engineer
GeorgiaTEK Systems Inc. is seeking a Platform Engineer with expertise in Azure, AKS, and Terraform. The role involves designing, deploying, and managing infrastructure solutions, particularly for AI/ML platforms, while ensuring scalability, security, and reliability.
Responsibilities
Design, deploy, and manage infrastructure solutions using Terraform, ensuring scalability, security, and reliability
Develop and maintain infrastructure as code scripts to automate the provisioning and configuration of resources
Ensure version-controlled, repeatable deployments using IaC best practices
Implement and manage Kubernetes clusters for containerized applications
Collaborate with development teams to deploy, scale, and optimize applications in Kubernetes environments
Leverage scripting languages (e.g Python) to automate routine tasks and streamline workflows
Implement continuous integration and continuous deployment (CI/CD) pipelines for efficient software delivery
Ensure seamless integration of infrastructure components with CI/CD pipelines
Design, deploy, and maintain scalable and reliable infrastructure for AI/ML platforms
Implement containerization (Docker) and orchestration (Kubernetes) solutions for deploying and managing AI/ML applications
Ensure containerized applications are secure, scalable, and easily deployable
Enable seamless integration of AI/ML models into the platform, ensuring data pipelines are efficient and reliable
Establish monitoring and alerting systems to ensure the health and performance of AI/ML platforms
Implement security best practices for AI/ML platforms, ensuring data privacy and compliance with industry standards
Qualification
Required
Expertise in Azure, AKS and Terraform
Design, deploy, and manage infrastructure solutions using Terraform, ensuring scalability, security, and reliability
Develop and maintain infrastructure as code scripts to automate the provisioning and configuration of resources
Ensure version-controlled, repeatable deployments using IaC best practices
Implement and manage Kubernetes clusters for containerized applications
Collaborate with development teams to deploy, scale, and optimize applications in Kubernetes environments
Leverage scripting languages (e.g Python) to automate routine tasks and streamline workflows
Implement continuous integration and continuous deployment (CI/CD) pipelines for efficient software delivery
Ensure seamless integration of infrastructure components with CI/CD pipelines
Design, deploy, and maintain scalable and reliable infrastructure for AI/ML platforms
Implement containerization (Docker) and orchestration (Kubernetes) solutions for deploying and managing AI/ML applications
Ensure containerized applications are secure, scalable, and easily deployable
Enable seamless integration of AI/ML models into the platform, ensuring data pipelines are efficient and reliable
Establish monitoring and alerting systems to ensure the health and performance of AI/ML platforms
Implement security best practices for AI/ML platforms, ensuring data privacy and compliance with industry standards