Staff Product Manager – Compute

Lambda

. Own a meaningful part of the future of compute delivery for Lambda customers .

Posted 10/9/2026full-timeUnited StatesLead💰 $291,000 - $430,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive product management experience in compute platforms, with a strong focus on GPU and CPU infrastructure, pricing strategies, and customer-centric product definitions. Capable of collaborating across teams to deliver integrated solutions while effectively communicating complex technical concepts.

Highest-signal resume keywords

Product Management ExperienceGPU And CPU InfrastructurePricing And Packaging StrategyCustomer Communication SkillsCompute Primitives Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Compute Platform ManagementProduct DefinitionUser Story CreationAcceptance Criteria DevelopmentCapacity EconomicsPerformance IsolationDistributed TrainingInfrastructure-As-CodeFailure HandlingPreemptible Capacity Management

Soft Skills

Plain CommunicationStrong WritingDecision-Making

Tools & Technologies

Public APIsMachine ImagesSnapshots

Industry Keywords

HyperscalerCloud ProviderCompute DeliveryOn-Demand GPU Instances1-Click Clusters

Tech Stack

Tools & technologies

Cloud

About the role

Key responsibilities & impact

Own a meaningful part of the future of compute delivery for Lambda customers
Define instance families, sizes, tenancy, capacity access and retention across GPUs and CPUs
Determine which mature compute-cloud capabilities matter for Lambda and which AI-specific capabilities are needed
Investigate customer needs through customers, deals, escalations, and support for On-Demand GPU Instances and 1-Click Clusters
Prioritize and sequence work, including explicitly deciding what Lambda will not do
Produce precise requirements, user stories, and acceptance criteria
Decide pricing, packaging, and commitment terms across NVIDIA GPU generations
Work with compute and control plane engineering teams and make tradeoff decisions during development
Establish launch criteria and coordinate documentation, pricing, sales, and support readiness
Define success metrics and measure adoption and utilization after launch
Document and maintain decisions on contested tradeoffs
Partner with product managers and storage, networking, orchestration, and commerce teams to deliver an integrated product
Collaborate with engineers, designers, executives, and partners to build product alignment and execution

Requirements

What you’ll need

7+ years of product management experience, including time on a compute platform at a hyperscaler, neocloud, or comparable cloud provider
Shipped compute primitives used by external customers at scale, such as instance types, capacity products, provisioning interfaces, or placement and isolation controls
Understanding of GPU and CPU infrastructure, including launch paths, hardware failure modes, placement, and performance
Experience owning products where day-two behavior mattered, including failure handling, maintenance, and customer communications during incidents
Experience owning pricing, packaging, or commitment terms for an infrastructure product
Ability to distinguish hyperscaler capabilities that transfer to an AI cloud from those that add cost without benefit
Ability to reason about utilization and capacity economics and balance customer flexibility with hardware utilization
Ability to define iterative plans from current state toward desired outcomes
Ability to turn ambiguous customer, technical, and commercial inputs into product definitions executed by multiple teams
Plain communication, strong writing, and decision-making skills
Experience with interruptible or preemptible capacity, reservations, or committed use products preferred
Experience with public APIs, infrastructure-as-code providers, machine images, or snapshots preferred
Experience with hardware failure handling across large hardware footprints preferred
Experience with performance isolation and placement on shared hardware preferred
Experience with bare metal or dedicated host products preferred
Experience with distributed training or large-scale inference workloads preferred
Must be able and willing to work onsite at the Bellevue or San Francisco office 4 days a week
Must be legally authorized to work in the United States

Benefits

Comp & perks

Generous cash & equity compensation
Health, dental, and vision coverage for you and your dependents
Wellness and commuter stipends for select roles
401k Plan with 2% company match (USA employees)
Flexible paid time off plan