Platform Engineer (Azure, AKS and Terraform)

ITTConnect•Seattle, WA

1d•Hybrid

About The Position

ITTConnect is seeking a Platform Engineer to join our team and work for one of our clients in the QSR business. Job location: Seattle, WA. Locals would be preferred , remote is OK.

Requirements

At least 10 years' total tech experience
Experience with Terraform, Azure and AKS
Proven experience in software/system/platform engineering, with a focus on AI tooling and integration.
Strong expertise in working with Azure
Proficiency in programming languages such as Python, Java, or C++.
Solid understanding of software development methodologies, including Agile and DevOps practices and tools for continuous integration and deployment.
Excellent problem-solving skills and the ability to work in a fast-paced, dynamic environment.
Strong communication and collaboration skills.

Nice To Haves

Experience in the QSR industry.

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