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Bellevue, Washington, United States
Onsite
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. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.
If you'd like to build the world's best AI cloud, join us.
Note: This position requires presence in our Bellevue or San Francisco office location 4 days per week; Lambda's designated work from home day is currently Tuesday.
About the Role
Storage and networking are what turn graphics processing units (GPUs) into a cloud. Customers come to Lambda for compute, then decide whether to stay based on where their data lives and whether the network gets it to the GPUs fast enough to keep them busy.
As a product manager on the Foundational Infrastructure team, you will own a meaningful part of defining where customer data lives on Lambda and how it gets to the GPUs. On storage, the domain covers where weights, checkpoints, and datasets sit, how customers get data in and keep it current, what performance they can count on when loading a model, and how capacity is metered and priced. On networking, it covers moving that data at the throughput training and inference demand, and the tenant isolation and virtual private cloud that enterprises require before they put production on us. It also covers how customers reach Lambda from their own networks, how traffic is balanced in front of serving endpoints, what egress they control, and how bandwidth is shared without one tenant starving another.
You will most likely work across both spaces rather than sit in one of them, following what customers need most at the time, alongside the other product managers on the team.
Most of this is the feature set a mature cloud already has and Lambda does not have yet. A neocloud is not a hyperscaler, though, and copying that list wholesale is the wrong instinct. Part of the job is judgment about which of those capabilities matter here and which carry cost we should not pay. The other part is that AI workloads move data in patterns these primitives were never designed for, and deciding where that difference should change the product is the more interesting half.
Great product managers at Lambda are defined by three things: insight, influence, and execution. Insight means you look at the data, determine what it means for customers and business, and then figure out what to do about it. But, a great idea doesn't mean anything in a vacuum. That is where influence comes in. Influence means you take that idea and get others to want to buy into it; you win over engineers, designers, executives, and partners without relying on authority. But a great idea that everyone is excited about doesn't matter unless it is delivered to customers. Execution means you work with the right people to get the idea launched, then measure and iterate. We hire product managers who learn new domains fast and reason rigorously from evidence. Deep storage or networking platform experience at a cloud provider is highly desired.
If you have built storage or network products at a cloud provider and want range across both rather than a single lane, we'd love to hear from you.
We value diverse backgrounds, experiences, and skills, and we are excited to hear from candidates who can bring unique perspectives to our team. If you do not exactly meet this description but believe you may be a good fit, please still apply and help us understand your readiness for this role.
What You'll Do
Find the Real Problem: Get close to customers, deals, escalations, and support on On-Demand GPU Instances and 1-Click Clusters, and work out what is actually blocking them on data and connectivity rather than what they asked for.
Decide What Matters: Rank and sequence the work in front of you across storage and networking, and be honest about what Lambda is not doing this year and why.
Write the Definition: Produce requirements, user stories, and acceptance criteria precise enough that engineering builds from them without a translation layer.
Price and Package It: Decide how storage and data transfer are metered, priced, and packaged across Lambda's public and private cloud offerings, and how customers compare the options.
Deliver With Engineering: Work through the build with the storage and networking teams, make the tradeoff calls that come up mid-flight, and keep scope honest against the date.
Land the Launch: Set launch criteria that cover the operational readiness an infrastructure product needs, and get documentation, pricing, sales, and support in place before it goes live rather than after.
Measure and Iterate: Define what success looks like before launch, then go find out whether it happened, using adoption and real workload performance rather than opinion.
Make the Call Stick: Take a position on contested tradeoffs, write it down well enough that people can disagree with it precisely, and keep owning the decision after it is made.
Work as a Group: Partner with the other product managers on foundational infrastructure and with the teams that own compute, orchestration, security, and commerce, so the pieces land as one product.
You
Have 7+ years of product management experience, including time on storage or networking products at a hyperscaler, neocloud, or comparable cloud provider.
Have shipped infrastructure products that external customers ran production workloads on, in object, file, or block storage, or in virtual networking, load balancing, or connectivity.
Have real depth in one of the two domains and enough range in the other to make decisions in it, plus the appetite to close that gap quickly.
Understand how data movement and network behavior show up as performance for distributed training and large-scale inference.
Have owned pricing, packaging, or metering for an infrastructure product.
Can tell which parts of a hyperscaler playbook transfer to an AI cloud and which are cost without benefit.
Able to define iterative plans that move an organization from the current state towards the desired outcome.
Can turn ambiguous customer, technical, and commercial inputs into product definition that multiple teams execute against.
Communicate plainly, write well, and make decisions easier for people who do not all share the same context.
Nice to Have
Experience with object storage and S3-compatible interfaces, or with parallel and shared file systems at high throughput.
Experience with block storage, snapshots, or the storage path behind instance boot and recovery.
Experience moving bulk data into a cloud, including resume, integrity verification, and throughput the customer can watch.
Experience with virtual private cloud networking, security groups, or private connectivity back to a customer's own network.
Experience with load balancing, controlled egress, or edge protection in front of production serving endpoints.
Experience with high performance fabrics for distributed training, like InfiniBand, remote direct memory access, or GPUDirect.
Salary Range Information
The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.
About Lambda
Founded in 2012, with 500+ employees, and growing fast
Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove
We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
Our values are publicly available: https://lambda.ai/careers
We offer 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 that we all actually use
Equal Opportunity Employer
Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
