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From the employer's careers site First seen 8 Nov 2026

Compute Systems Architect - Expeditionary AI/HPC Data Centers

Salary

$146,000-$222,000 USD per year

Apply on Anduril Industries

Description

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology.

Anduril Expeditionary Systems (AES) is building AI Factories and Command/Control centers,specialized, high-performance computing centers designed to process petabyte-scale data and convert it into decisions at machine speed from forward operating bases.

We are seeking a High Performance Compute Systems Architect to design and build these tactical AI/HPC data centers from the ground up.

Responsibilities

  • Own the end-to-end architecture of AI Factory tactical data centers from compute hardware through power architecture, networking, and thermal cooling systems
  • Design GPU-accelerated compute clusters optimized for AI inference and training workloads at the tactical edge (NVIDIA H100/A100, AMD MI300, or similar)
  • Engineer advanced thermal solutions for high-density compute without traditional data center infrastructure (liquid cooling, immersion cooling, hybrid systems)
  • Design air-transportable, modular systems (containerized, palletized, vehicle-mounted) that are rapidly deployable and operationally credible
  • Build infrastructure optimized for austere and contested environments,extreme temperatures, limited grid power, SCIF-accreditable, electromagnetic hardening
  • Work in tight coupling with Lattice and AI/ML teams to ensure physical infrastructure meets mission-critical software requirements
  • Partner with defense customers to translate operational requirements and needs into technical architectures
  • Lead prototyping, field testing, and operational validation through military exercises and real-world deployments
  • Drive systems from concept through production at scale, working across hardware, software, supply chain, and program teams
  • Define standards and best practices for tactical AI compute infrastructure across AES product lines

Required Qualifications

  • Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related technical field
  • 5+ years of experience designing and deploying data center infrastructure, HPC clusters, large-scale compute systems, or tensor / accelerator compute nodes.
  • 8+ years of engineering experience designing and deploying electrical products
  • Deep expertise in GPU-accelerated computing architecture for AI/ML workloads (NVIDIA, AMD, or similar platforms)
  • Strong understanding of power distribution systems for high-density compute including PDUs, power shelves, UPS systems, generators, chillers, power distribution, and energy management
  • Experience with thermal management for high-power-density systems,liquid cooling and chiller systems.
  • Proven track record building and deploying production infrastructure from concept through operational scale
  • Systems thinking ability to optimize across competing constraints (performance, power, thermal, weight, cost, reliability)
  • U.S. Person status required (U.S. citizen, permanent resident, refugee, or asylee)
  • Ability to obtain and maintain a U.S. security clearance (U.S. citizenship may be required)
  • Must be able to travel up to 15% of the time

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Skills

Required

  • GPU-accelerated computing
  • AI/ML
  • data center infrastructure
  • HPC clusters
  • electrical engineering
  • thermal management
  • power distribution systems
  • energy management

Nice to have

  • AI/ML infrastructure
  • computer vision
  • autonomous systems
  • edge computing
  • distributed inference systems
  • autonomous vehicles
  • 3-phase power distribution
  • HV battery systems
  • tactical military systems
  • ruggedized computing
  • deployable infrastructure

Ready to apply?

You apply with the employer directly. Their original posting is here: https://job-boards.greenhouse.io/andurilindustries/jobs/5285298007

Apply on Anduril Industries