The opportunity
Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers.
What you'll do
Track the Roadmap: Stay far enough ahead of where NVIDIA's hardware and software is going that Lambda can plan against it rather than react to it.
Decide What Lambda Takes From NVIDIA: Call which of their new hardware and software Lambda should productize into On-Demand GPU Instances, 1-Click Clusters, and private cloud deployments, and which to pass on, with the reasoning written down.
Turn Adoption Into Product: Take what Lambda adopts from NVIDIA the whole way into something customers can buy, including packaging, pricing, and launch criteria.
Own the Relationship: Be the single point of contact both companies call. Route incoming requests to the right product and engineering owners and close the loop rather than letting things sit.
Run the Joint Work: Own the product side of what the two companies build together, including scope and what done means.
Bring the Partner View to Hardware: Work alongside Lambda's hardware product managers as new NVIDIA GPU generations move from evaluation into production, so the platform decisions they own are made with the best picture of what is coming.
What they're looking for
- Write the Definition: Turn what comes out of the relationship into requirements, user stories, and acceptance criteria Lambda engineering can build from without a translation layer.
- Say No Clearly: Tell a partner what Lambda will not do and why, early and plainly enough that the relationship is better for it rather than worse.
- Measure the Call: Decide what a good adoption decision looks like before you make it, then go back and check whether it paid off.
- Work as a Group: Partner with the product managers who own compute, storage, networking, orchestration, and security, since most of what comes through this relationship lands in their areas.
