Summary
Georgia IT, Inc. is seeking a Platform Engineer with expertise in Kubernetes, Terraform, and Azure. The primary responsibilities include designing and managing infrastructure solutions, implementing CI/CD pipelines, and ensuring the security and scalability of AI/Client platforms.
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/Client platforms
- Implement containerization (Docker) and orchestration (Kubernetes) solutions for deploying and managing AI/Client applications
- Ensure containerized applications are secure, scalable, and easily deployable
- Enable seamless integration of AI/Client models into the platform, ensuring data pipelines are efficient and reliable
- Establish monitoring and alerting systems to ensure the health and performance of AI/Client platforms
- Implement security best practices for AI/Client platforms, ensuring data privacy and compliance with industry standards
Skills
- 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/Client platforms
- Implement containerization (Docker) and orchestration (Kubernetes) solutions for deploying and managing AI/Client applications
- Ensure containerized applications are secure, scalable, and easily deployable
- Enable seamless integration of AI/Client models into the platform, ensuring data pipelines are efficient and reliable
- Establish monitoring and alerting systems to ensure the health and performance of AI/Client platforms
- Implement security best practices for AI/Client platforms, ensuring data privacy and compliance with industry standards
Qualifications
Must Haves
- 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/Client platforms
- Implement containerization (Docker) and orchestration (Kubernetes) solutions for deploying and managing AI/Client applications
- Ensure containerized applications are secure, scalable, and easily deployable
- Enable seamless integration of AI/Client models into the platform, ensuring data pipelines are efficient and reliable
- Establish monitoring and alerting systems to ensure the health and performance of AI/Client platforms
- Implement security best practices for AI/Client platforms, ensuring data privacy and compliance with industry standards