Design, deploy, and manage infrastructure solutions using Terraform, focusing on scalability, security, and reliability. Implement best practices for version-controlled, repeatable deployments using Infrastructure as Code (IaC).
Numbers & Facts
Location
Seattle, WA (Remote)
Description
Platform Engineer - Kubernetes / Terraform / Azure Location – Seattle, WA (remote - PST) Position Type: Contract
US Citizen, Green Card,TN, GC EAD and H4 EAD only No Third-party agencies.
Responsibilities:
Design, deploy, and manage infrastructure solutions using Terraform, focusing on scalability, security, and reliability.
Develop and maintain infrastructure as code scripts to automate resource provisioning and configuration.
Implement best practices for version-controlled, repeatable deployments using Infrastructure as Code (IaC).
Manage and implement Kubernetes clusters for containerized applications.
Collaborate with development teams to deploy, scale, and optimize applications within Kubernetes environments.
Utilize scripting languages, such as Python, to automate routine tasks and streamline workflows.
Ensure the seamless integration of infrastructure components with Continuous Integration/Continuous Deployment (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 the security, scalability, and easy deployability of containerized applications.
Facilitate the integration of AI/Client models into the platform, ensuring efficient and reliable data pipelines.
Establish monitoring and alerting systems to ensure the health and performance of AI/Client platforms.
Qualifications:
Proven experience in designing and managing infrastructure solutions using Terraform.
Strong proficiency in developing and maintaining Infrastructure as Code (IaC) scripts.
Experience in managing Kubernetes clusters for containerized applications.
Proficient in scripting languages, particularly Python, for automation.
Familiarity with containerization (Docker) and orchestration (Kubernetes) for AI/Client applications.