AI Cloud Infra Lead

AEP; Gahanna, Northern (OH, KY); Hybrid; USD 137,000 - 178,000; Full time

Job summary

AEP is seeking an Infrastructure Engineer Lead to design, build, and operate secure, scalable cloud and on-prem AI infrastructure in Gahanna, OH. You will own AWS foundations, Kubernetes clusters, and cost controls while partnering with security, architecture, and data teams to deliver production-ready platforms.

The role requires deep AWS expertise, strong Kubernetes operations, and a track record of implementing cost management, monitoring, and governance for AI workloads.

Qualifications

• Bachelor's degree in computer science, engineering, or related technical field.
• 12 years of relevant work experience required.
• Strong hands-on engineering in AWS, IAM, VPC, compute, storage, encryption/KMS, and account structure.

Responsibilities

• Design, build and maintain AWS account structure, landing zones, and AI workload patterns.
• Engineer compute, storage, and networking foundations for AI workloads, including GPU instances.
• Enable and operate AI platform services such as Bedrock and SageMaker with governance.
• Create IaC modules and pipelines to enable rapid deployment with guardrails.
• Design, build and maintain on-prem AI infrastructure for edge and disconnected environments.
• Implement monitoring, logging, patching, backup and recovery processes for AI infra.
• Collaborate with security, architecture, and compliance to meet standards.
• Provide training and mentorship to engineers on the team.

Skills

AWS IAM

VPC Networking

Kubernetes

Networking fundamentals

Terraform

CI/CD pipelines

Security & Compliance

Monitoring & Cost

Analytical skills

Communication

Education

Bachelor's degree

Tools

Terraform

Ansible

Python

PowerShell

Job description

AEP is seeking an Infrastructure Engineer Lead to design, build, and operate secure, scalable cloud and on-prem AI infrastructure in Gahanna, OH. You will own AWS foundations, Kubernetes clusters, and cost controls while partnering with security, architecture, and data teams to deliver production-ready platforms.

The role requires deep AWS expertise, strong Kubernetes operations, and a track record of implementing cost management, monitoring, and governance for AI workloads.