Camps

AI Infrastructure Engineer

Build the systems that run the AI boom.

The AI boom is not about models. It is about the infrastructure that trains and serves them. We train engineers to build and run GPU clusters, AI fabric networking, and distributed training platforms at the scale that frontier labs and GPU clouds require.

$99.99/mo | starts Q2 2027

What you will be able to do

• GPU fleet operations: DCGM, NVML, MIG, driver and firmware lifecycle
• AI fabric networking: RoCEv2, InfiniBand, NCCL topology, Spectrum-X
• Distributed training orchestration: Slurm, Kubernetes GPU operator, Kubeflow
• Inference platforms: vLLM, TGI, Triton, autoscaling and cost tuning
• Parallel storage for training: Lustre, WekaFS, GPFS
• Observability: DCGM Exporter, Prometheus, NVLink throughput, job failure analysis

Why AI Infrastructure Engineer demand is exploding.

The AI boom runs on infrastructure, and there are not enough people who can build it.

• $185K Median global salary per Refonte Learning 2026 report. Top 10% earn $250K+. Big Tech senior comp reaches $350K+ with equity.
• #1 Fastest-growing role on LinkedIn's 2026 Jobs on the Rise report. AI engineer has held the top spot two years running.
• 1.3M Projected US AI job openings over the next two years, with supply covering fewer than 645K candidates. Structural deficit.

The AI boom is not about model research. It is about the infrastructure that trains and serves models at scale. NVIDIA makes the chips. CoreWeave, Lambda, and Crusoe run the GPU clouds. Someone has to build the Kubernetes clusters, operate the RoCE and InfiniBand fabrics, manage H100 and Blackwell fleets, and keep training jobs running across thousands of GPUs. That someone is an AI Infrastructure Engineer.

The scale is not hypothetical. CoreWeave signed a $21B infrastructure deal with Meta through 2032, a multi-year agreement with Anthropic for Claude inference, and Deloitte projects AI infrastructure budgets will triple by 2028. Hiring keeps lagging. Companies pay 18.7% above standard market rate for engineers with this specific skill stack.

The pattern that wins is operator-first: engineers who already ran bare metal at scale, then learned the GPU and AI fabric layer on top. CDN and hyperscaler veterans are the exact supply that frontier labs and GPU clouds hire from. This is the ladder we train you for.

Employers hiring for this work include CoreWeave, NVIDIA, Lambda, Crusoe, Together AI, Anthropic, OpenAI, xAI, Meta AI Infra, Google Cloud AI.

Reported pay for this role runs $150K - $400K+. Market data, not guaranteed outcomes.

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