Staff Product Manager - Storage & Networking
Staff Product Manager on Lambda's Foundational Infrastructure team, defining how customer data is stored, priced, and delivered to GPUs on the AI cloud, plus the networking, VPC, and connectivity around it. Needs 7+ years of PM experience, ideally on cloud storage or networking products, working onsite in Bellevue or San Francisco 4 days/week.
- Compensation
- $291K–$387K / yr
- Location
- Bellevue Office
- Work setup
- Hybrid
- Seniority
- Staff
- Employment
- Not specified
- Experience
- 7+ years
- Category
- Product
- Posted
Skills
Must have
- 7+ years of product management experience, including time on storage or networking products at a hyperscaler, neocloud, or comparable cloud provider
- Shipped infrastructure products external customers ran production workloads on, in object, file, or block storage, or virtual networking, load balancing, or connectivity
- Real depth in one of the two domains (storage or networking) and enough range in the other to make decisions in it
- Understand how data movement and network behavior show up as performance for distributed training and large-scale inference
- 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 current state towards desired outcome
- Can turn ambiguous customer, technical, and commercial inputs into product definition multiple teams execute against
- Communicates plainly, writes well, and makes decisions easier for people who do not share the same context
- Presence in the Bellevue or San Francisco office 4 days per week
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 observable throughput
- Experience with virtual private cloud networking, security groups, or private connectivity to customer networks
- 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, RDMA, or GPUDirect
Full description
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.