N+1 recruits the AI, data, and software engineers who turn a data center full of GPUs into a product. It is the natural other half of a data center practice: we staff the building, and the workloads that run inside it.
A data center exists to run compute. Our Critical Facilities practice keeps the building alive. This practice staffs the people who make the compute productive, from the models to the platform they run on.
Builds, trains, and ships the models that power intelligent products.
Role · liveOwns products built on models, from eval sets to launch.
Role · liveBuilds the pipelines and warehouses that feed every model.
Role · liveFrames the problem and builds the model or analysis to answer it.
Role · liveRuns models in production and owns the platform they live on.
Role · liveBuilds the applications and control planes on top of the infrastructure.
| Role | Base range | Senior / top total comp |
|---|---|---|
| AI / ML Engineer | $134k - $193k | $350k - $795k+ (frontier) |
| AI Product Manager | $150k - $230k | $250k - $550k |
| Data Engineer | $130k - $137k avg | $300k - $420k+ |
| Data Scientist | $112k - $155k | $330k+ |
| MLOps / Platform | $130k - $165k avg | $300k+ |
| Full-Stack / Software | $110k - $180k | $600k+ (frontier) |
Figures blended from Built In, Robert Half, Glassdoor, Indeed, levels.fyi, BLS, and KORE1 2026 data. Each role page carries the detail and citations. See the full salary guide for the facilities side of the stack.
Whether you need a critical facilities engineer to keep the site online or an ML engineer to make the compute pay, one specialist partner covers both, on contract, direct hire, or fractional terms.