Senior AI Infrastructure Engineer, Physical Infrastructure

Anduril Industries; Seattle (WA); On-site; USD 166,000 - 220,000; Full time

Benefits offered by this job

Equity grants

Top-tier benefits (health, recovery)

Job summary

Anduril Industries is seeking a Senior AI Infrastructure Engineer to own and scale our GPU training infrastructure. You will lead stability, automation, and high‑performance networking across multi‑team research and engineering programs.

Focus areas include NCCL, Run:AI, Kubernetes, and advanced interconnects. This hands‑on role demands physical datacenter work and TS clearance eligibility, in a fast‑moving defense tech environment.

Qualifications

• 10+ years in hands-on infrastructure, HPC, or datacenter engineering supporting GPU compute at scale.
• Hands-on with H200/B200/B300 GPUs: bring up, cabling, firmware/driver management.
• Experience with high-performance interconnects in large GPU clusters.
• Experience with high-performance storage and parallel file systems.
• Kubernetes required; Run:AI or similar GPU scheduling experience preferred.
• Strong automation; build repeatable deployment pipelines.
• Able to lift 50+ lbs and perform physical datacenter work.
• Eligible to obtain and maintain active U.S. Top Secret clearance.

Responsibilities

• Rack, stack, cable, and bring up GPU compute hardware and topology.
• Build and tune interconnect fabric for hundreds of GPUs.
• Integrate high-performance parallel storage for large datasets.
• Automate cluster deployment and configuration via infrastructure as code.
• Operate and extend Kubernetes/Run:AI for GPU scheduling and multi-tenant workloads.
• Own fleet health: monitoring, alerting, rapid triage of hardware/software faults.
• Onboard engineers and researchers; assist with workloads and debugging.
• Partner with product teams to translate compute needs into platform capability.

Skills

10+ years experience

GPU compute at scale

H200/B200/B300

NVIDIA NVL72

NVLink

InfiniBand

RoCE

Kubernetes

Run:AI

Automation

Tools

Kubernetes

Run:AI

NCCL

NVLink

InfiniBand

RoCE

Specturm-X

VAST

Weka

Lustre

Job description

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

ABOUT THE TEAM

CorpTech Infrastructure Engineering builds and operates the foundational infrastructure that powers Anduril at large. We give engineers, researchers, and product teams across the company a place to deploy fast, scalable infrastructure without having to become infrastructure experts themselves. As Anduril’s AI and autonomy ambitions grow, our team is responsible for delivering the next generation of compute, networking, and storage capabilities that make cutting edge model training and inference possible company wide.

ABOUT THE JOB

We’re looking for a Senior AI Infrastructure Engineer to lead the vision, execution, and long-term stability of how Anduril trains with GPUs at scale. In this role, you will take absolute ownership of cluster robustness, ensuring our high-performance GPU systems are highly available, fault-tolerant, and resilient for ML platform and research teams company-wide. This is a highly hands-on role where your primary focus is logical stability and automated resilience—building self-healing mechanisms to proactively detect and isolate hardware faults, tuning NCCL and high-speed networking, and optimizing Kubernetes, Run:AI, and Ray scheduling. By replacing manual triage with automated deployment tooling and deep observability, you will ensure our massive-scale training infrastructure runs seamlessly and scales without linear headcount growth.

WHAT YOU’LL DO

• Rack, stack, cable, and bring up GPU compute (H200/B200/B300, NVL72) including physical topology, power, cooling, firmware/BIOS, and burn in validation.
• Build and tune the interconnect fabric (NVLink, InfiniBand, RoCE, Spectrum-X) connecting hundreds of GPUs into low latency training and inference clusters.
• Integrate high performance parallel storage (VAST, DDN, Weka) to sustain the throughput demanded by distributed training and terabyte scale multi modal datasets across Anduril’s programs.
• Automate cluster deployment and configuration end to end, including infrastructure as code for bring up, firmware/driver management, and fabric config, so new capacity comes online with minimal manual work.
• Operate and extend our Kubernetes/Run:AI environment for GPU scheduling, quota management, and multi tenant workload isolation across research and engineering teams company wide.
• Own fleet health: monitoring, alerting, and rapid triage of hardware and network faults (bad transceivers, GPU Xid errors, NCCL/collective failures, RoCE congestion).
• Onboard engineers and researchers onto the platform and act as their escalation point, working directly alongside them to debug, train, and optimize their workloads whenever infrastructure, not the model, is the bottleneck.
• Partner with product facing teams across Anduril to understand emerging compute needs and translate them into platform capability.

REQUIRED QUALIFICATIONS

• 10+ years in a hands on infrastructure, HPC, or datacenter engineering role supporting GPU compute at scale.
• Hands on experience with H200/B200/B300 (or comparable) GPU systems: bring up, cabling, firmware/driver management.
• Experience with high performance interconnects (NVLink, InfiniBand, RoCE, Spectrum-X) in clusters of hundreds of GPUs.
• Experience with high performance parallel storage (VAST, DDN, Weka, Lustre, or similar).
• Kubernetes required; Run:ai or similar GPU scheduling/orchestration experience strongly preferred.
• Strong automation background. You build repeatable, automated deployment pipelines rather than manual processes.
• Able to lift/move 50+ lbs and perform physical datacenter work (rack/stack/cable/troubleshoot).
• Eligible to obtain and maintain an active U.S. Top Secret clearance.

PREFERRED QUALIFICATIONS

• Experience with NVIDIA NVL72 rack scale systems.
• Experience supporting LLM token serving/inference infrastructure alongside training clusters.
• Network fabric tuning experience (congestion control, adaptive routing, QoS) for RoCE/InfiniBand at scale.
• Familiarity with GPU/network observability tooling (DCGM, fabric telemetry) and automated fault detection.
• Experience supporting infrastructure as a shared platform serving multiple internal customer teams with differing requirements.

US Salary Range

$166,000—$220,000 USD

The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril’s total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:

Benefits

At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next.

For more information, Explore Our Benefits.

Data Privacy

To view Anduril’s candidate data privacy policy, please visit https://anduril.com/applicant-privacy-notice/.

By submitting your application, you consent to Anduril Industries using a third-party service provider to conduct pre-employment risk, integrity, and due diligence screening and assessing potential risks as part of your application process. This third-party service provider provides risk-intelligence services that may include analysis of sanctions and watchlists, adverse media, public-record information, and other lawful open-source or commercial data sources. This third-party service provider does not act as a consumer reporting agency. Use of this provider helps to ensure compliance with applicable laws and protect technology, intellectual property, and organizational security.