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Anduril

Robot type
Drone · Defense
Location
Costa MesaCaliforniaUSA
Job type
Artificial Intelligence
Posted
Sep 3, 2026
Salary
$166,000–$220,000 a year
Full-time

Senior AI Infrastructure Engineer, Physical Infrastructure

Job description

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.

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.

Job responsibilities

  • 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…
  • Partner with product facing teams across Anduril to understand emerging compute needs and translate them into platform capability.

Job requirements

  • 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.
Apply on Anduril websiteSave

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