Compute Product Manager (AI)

Location: Hybrid, with presence in the Bellevue or San Francisco office four days per week; Tuesday is the designated work-from-home day.

Annual salary: $291,000–$387,000 in Bellevue or $323,000–$430,000 in San Francisco/San Jose.

Company

Lambda builds AI cloud infrastructure and provides GPU and CPU compute products for AI researchers, enterprises, and hyperscalers.

What you will do

• Define the future of compute products, including instance families, sizes, tenancy, capacity access, placement, performance isolation, hardware failure handling, maintenance, and operational signals.
• Investigate customer needs across On-Demand GPU Instances and 1-Click Clusters and prioritize the highest-impact problems.
• Write product requirements, user stories, and acceptance criteria for engineering teams.
• Own pricing, packaging, and commitment models across NVIDIA GPU generations.
• Partner with compute, control plane, storage, networking, orchestration, and commerce teams to deliver and launch products.
• Set launch criteria, prepare documentation and go-to-market readiness, and measure adoption and utilization after launch.

Requirements

• 7+ years of product management experience, including work on a compute platform at a hyperscaler, neocloud, or comparable cloud provider.
• Experience shipping compute primitives used at scale, such as instance types, capacity products, provisioning interfaces, or placement and isolation controls.
• Strong understanding of GPU and CPU infrastructure, including launch paths, hardware failures, placement, and performance.
• Experience owning day-two product behavior, failure handling, maintenance, customer communication, pricing, packaging, or commitment terms.
• Ability to reason about utilization, capacity economics, customer flexibility, and infrastructure tradeoffs.
• Clear written and verbal communication, structured decision-making, and the ability to turn ambiguous inputs into executable product definitions.

Nice to have

• Experience with interruptible or preemptible capacity, reservations, or committed-use products.
• Experience with public APIs, infrastructure-as-code providers, machine images, or snapshots.
• Experience with hardware failure handling, performance isolation, placement, bare metal, or dedicated host products.
• Experience with distributed training or large-scale inference workloads.

Culture & Benefits

• Diverse backgrounds, experiences, and perspectives are valued.
• Cash and equity compensation.
• Health, dental, and vision coverage for employees and dependents.
• Wellness and commuter stipends for select roles.
• 401(k) plan with a 2% company match for US employees.
• Flexible paid time off.