Senior Data Center Infra Engineer – AI Cloud Platform

Designworks Talent LLC; Bellevue (KY); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) with company match

Paid holidays

Job summary

Designworks Talent LLC is sourcing for a Data Center Infrastructure Software Engineer to join a Bellevue-based hybrid team. You will design, deploy, and optimize a scalable AI infrastructure, spanning compute, networking, storage, and automation.

You will work on Kubernetes deployment, infrastructure automation, and performance tuning for large-scale workloads across data centers, with opportunities to influence architecture and tooling.

Qualifications

• 5+ years of experience designing, building, or operating large-scale Linux-based infrastructure.
• Hands-on experience with Kubernetes, containerization, and distributed systems in production environments.
• Experience with infrastructure-as-code and automation tools such as Terraform, Ansible, or similar frameworks.
• Strong experience operating cloud or datacenter-scale infrastructure.

Responsibilities

• Develop infrastructure-as-code, automation, and provisioning systems for compute, networking, and storage.
• Deploy and optimize Kubernetes, container, and distributed computing platforms.
• Optimize GPU, networking, storage, and system performance for large-scale AI workloads.
• Troubleshoot complex issues across hardware, operating systems, networking, storage, and software stacks.
• Build reliability, observability, and operational excellence practices for mission-critical infrastructure.

Skills

Linux

Kubernetes

Terraform

Ansible

Distributed systems

Tools

MAAS

Ironic

PXE

Redfish

xCAT

Job description

Designworks Talent LLC is sourcing for a Data Center Infrastructure Software Engineer to join a Bellevue-based hybrid team. You will design, deploy, and optimize a scalable AI infrastructure, spanning compute, networking, storage, and automation.

You will work on Kubernetes deployment, infrastructure automation, and performance tuning for large-scale workloads across data centers, with opportunities to influence architecture and tooling.