AI Infrastructure Engineer

Why Nuclearn.ai

Nuclearn.ai builds AI-powered software for the nuclear and utility industries—tools that keep critical infrastructure reliable, efficient, and safe. Our software integrates AI-driven workflow, documentation, and research automation, and is already used at 60+ nuclear reactors across North America. You'll ship production code operators and engineers rely on every day.

We're growing quickly, expanding our team and our Phoenix HQ. The work is consequential: what you build helps real plants run safer and smarter.

U.S. citizenship or permanent residency (green card) is required due to DOE export compliance.

• Own AI hardware architecture end-to-end. Design GPU/CPU systems that deliver consistent, high-performance AI workloads. Define storage, networking, container runtime, and OS standards in partnership with ML and platform engineering teams.
• Run and scale our Phoenix AI data center. Manage rack architecture, power/cooling constraints, redundancy, monitoring, firmware lifecycle, and capacity planning. Identify bottlenecks early and fix them before they impact production.
• Partner directly with utility IT teams. Analyze and validate customer infrastructure intended to host Nuclearn applications. Conduct architecture reviews, confirm configuration alignment, and prevent GPU/runtime incompatibilities before go-live.
• Drive hardware lifecycle evolution. Plan GPU refreshes, expansion pathways, and just-in-time capacity upgrades to ensure infrastructure keeps pace with model complexity and platform growth.

• Develop and publish a clear AI hardware requirements standard for both internal deployment and customer-facing environments — including GPU sizing models, storage thresholds, networking requirements, and supported configurations.
• Analyze and validate a utility customer's proposed infrastructure architecture before deployment — identifying performance gaps, GPU/runtime misalignment, or security configuration issues and providing concrete remediation guidance.
• Audit the Phoenix data center and execute just-in-time infrastructure upgrades — adding GPU capacity, expanding storage, or rebalancing workloads to maintain sustained high-performance AI execution as usage scales.

• Degree in Computer Engineering, Electrical Engineering, Computer Science, or equivalent practical experience
• Proficiency in Linux server administration and GPU-based AI systems
• Strong experience deploying and tuning NVIDIA GPU environments for ML workloads
• Familiarity with containerized runtimes (Docker, Kubernetes) and AI model hosting
• Excellent troubleshooting skills at the hardware/software boundary
• Ability to operate independently in a fast-moving, high-ownership startup environment

• Experience in utility IT, energy infrastructure, or other regulated industries
• Experience supporting on-prem or air-gapped environments
• Prior responsibility for production data center operations
• Familiarity with cybersecurity expectations common to critical infrastructure environments

• Establish a standardized AI hardware reference architecture used across all deployments
• Build a scalable infrastructure refresh strategy that prevents hardware drift and obsolescence
• Make AI infrastructure a strategic advantage — stable, scalable, and trusted by customers

• Base salary: $120k - $165k
• Equity:
  0.025% - 0.125%
• Benefits:
  Unlimited PTO, health/dental/vision insurance, 4% 401k match

• Full-time, salaried
• Mon–Fri hybrid (Wed remote); expectation is ≥80% in-office (Phoenix HQ)

• 20-min intro with the founder/hiring manager to trade context and assess mutual fit
• Practical work sample (60–90 min; a real task in our stack)
• Team meet + peer programming (system design + collaboration) We aim to move from first chat to decision quickly.