Staff AI/GPU Cloud Engineer

Micron•Boise, ID

About The Position

Micron Technology is seeking a Cloud Platform Engineer for its Cloud Platform Engineering team, which builds secure, scalable, and resilient multi-cloud infrastructure for business-critical applications, AI initiatives, and enterprise services. The team partners with Security, Infrastructure, Data, Application Development, and AI teams to deliver automated cloud platforms, GPU-enabled compute environments, and modern operational capabilities across AWS, Azure, and GCP. The role designs, implements, automates, and supports secure cloud platforms across AWS, Azure, and GCP. Its focus includes cloud architecture, Infrastructure-as-Code, automation, AI enablement, GPU infrastructure, and operational excellence while maintaining security, scalability, and governance standards. Micron describes its benefits as supporting employee wellbeing and professional growth. Available benefits include medical, dental, and vision plans, income-protection programs for illness or injury, paid family leave, paid time off, and paid holidays. Micron is an equal opportunity workplace and affirmative action employer.

Requirements

At least 5 years of experience designing, implementing, and supporting cloud solutions in at least two major public cloud platforms: AWS, Azure, and/or GCP.
At least 3 years of hands-on experience with Infrastructure-as-Code tools such as Terraform, CloudFormation, ARM, or Bicep.
At least 3 years of scripting and automation experience using Python, PowerShell, or equivalent programming languages.
Experience building and supporting CI/CD pipelines and automating cloud operations in enterprise environments.
Experience deploying and managing cloud networking, security controls, IAM, governance frameworks, and hybrid connectivity solutions.

Nice To Haves

Experience deploying and supporting AI, machine learning, or generative AI workloads in cloud environments.
Hands-on experience managing GPU-based infrastructure for AI/ML training and inference workloads.
Experience demonstrating AI services, LLMs, AI agents, or cloud-native AI platforms to automate operations and infrastructure management.
Experience with Kubernetes and containerized platform operations in large-scale cloud environments.
Strong architecture, platform engineering, and collaboration experience, including participation in architecture reviews and Agile delivery teams.

Responsibilities

Design, deploy, and operate secure, scalable cloud infrastructure and platform services across AWS, Azure, and GCP.
Develop and maintain Infrastructure-as-Code, automation frameworks, and CI/CD pipelines using Terraform, CloudFormation, Python, and PowerShell.
Support enterprise AI, machine learning, and GPU-based workloads by managing compute platforms, capacity, performance, and operational readiness.
Implement cloud security controls, governance policies, monitoring solutions, and resiliency processes to ensure platform stability and compliance.
Collaborate with infrastructure, security, data, and application teams to define platform standards, review architectures, and drive continuous improvement initiatives.