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# Infrastructure Engineer (GPU & Compute)

- **Company:** Lightning AI
- **Location:** Tonawanda, NY, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Systems Engineering, Intelligent Platform Management Interface, Data Centers, Software Debugging, Linux, Firmware, IBM Hardware Management Console, Image Management, InfiniBand, Python (Programming Language), Linux System Administration, System Software, System Testing, Virtualization Technology, Graphics Processing Unit (GPU), High Performance Computing, Information Technology, Bare Metal
- **Published:** November 8, 2026
- **Apply:** https://www.juju.com/job/28_25303_9f67a1b4e80012979e5f5d12e669d713

## About the Role

* 5+ years of experience in infrastructure engineering, systems engineering, or related roles
 * Strong Linux systems experience in production environments
 * Hands-on experience with GPU-enabled systems and tools such as NVIDIA DCGM
 * Familiarity with bare-metal provisioning and system bring-up workflows
 * Proficiency in Python or similar scripting/programming languages for automation
 * Ability to debug complex issues across hardware, OS, GPUs, and system software

Ideal Experience

 * Experience with high-performance interconnects (e.g., InfiniBand, NVLink)
 * Experience with PXE boot environments, LiveCD systems, or image-based provisioning workflows
 * Experience with hardware management interfaces such as iDRAC, IPMI, or Redfish
 * Data center operations experience, including working with physical hardware
 * Experience supporting AI/ML or HPC workloads at scale
 * Experience with GPU validation frameworks or large-scale hardware qualification processes

## Description

In this role, you will help bring up, validate, and operate large-scale bare-metal compute infrastructure, with a particular focus on GPU-enabled systems. You will work at the intersection of hardware, systems, and software-owning system diagnostics and validation, developing automation, improving reliability, and ensuring clusters are ready to support demanding AI/ML and HPC workloads.
You will play a key role in GPU and system-level qualification, running validation environments and test clusters, and improving the tooling and workflows that support infrastructure bring-up at scale. This includes owning and evolving our image pipeline alongside provisioning and validation systems to ensure our infrastructure is consistent, performant, and reliable from day one.

This role is based in one of our hubs (NYC, SF, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time., * Own and evolve systems for image management, deployment, and validation across bare-metal infrastructure

 * Run and maintain test clusters used for system validation, diagnostics, and bring-up
 * Validate firmware, drivers, and OS images across compute and GPU-enabled systems
 * Support hardware qualification efforts for next-generation platforms, * Diagnose and resolve complex issues across GPUs, drivers, OS, and hardware layers
 * Analyze system and GPU performance using tools such as NVIDIA DCGM
 * Identify failure patterns and drive improvements in system stability and validation coverage

Automation & Tooling

 * Build and maintain automation for provisioning, validation, and system bring-up
 * Develop Python-based tools and workflows to improve efficiency and reduce manual operational overhead
 * Improve the reliability, repeatability, and scalability of image pipelines and validation systems

Systems & Operations

 * Manage and operate Linux-based systems in production and validation environments
 * Manage virtualization technology
 * Support bare-metal provisioning workflows, including PXE and image-based systems
 * Interface with hardware management systems (e.g., IPMI, Redfish) for monitoring and debugging

Cross-Functional Collaboration

 * Partner with Infrastructure, Hardware, and Data Center teams on system bring-up and validation
 * Collaborate with platform and ML teams to ensure systems meet workload requirements
 * Contribute to best practices for provisioning, diagnostics, and lifecycle management of infrastructure