The opportunity
Runpod is the AI Developer Cloud. More than one million developers, from indie researchers to teams running frontier models in production, use Runpod to experiment, train, fine-tune, deploy, and scale AI on one platform.
What you'll do
Maintain a live view of available capacity across GPU types and datacenters,: and serve as the company's source of truth for what we have, what's sold, and what's coming.
Drive fill on upcoming tranches of capacity, partnering with Sales and: Infrastructure to line up committed demand ahead of bring-up.
Monitor utilization across the existing fleet, flagging underperforming SKUs,: datacenters, and node groups and driving the pricing or placement changes that fix them.
Evaluate alternate methods of GPU ownership: revenue share, leasing, and direct purchase — and recommend the right structure for each opportunity.
Forecast cash requirements for new capacity commitments and existing lease: renewals, and own the capacity capex plan.
Model the revenue impact of bring-up timing, tracking schedule slippage: against plan and quantifying the cost of delay.
What they're looking for
- Evaluate and monitor non-GPU infrastructure investments, including storage and CPU capacity.
- Build the unit economics of the fleet: contribution margin by GPU type, datacenter, and host — and set the pricing floors and return hurdles that capacity decisions are measured against.
- Support commercial negotiations with hosts and datacenter partners, modeling: term sheets, revenue-share splits, and lease economics.
- Run scenario and risk analysis on the supply book, including GPU price: deflation, the contract expiration ladder, host and datacenter concentration, and residual value or redeployment of aging SKUs.