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 You own product management for compute, storage, and networking at Lambda, which is the core of what Lambda sells. Engineering owns the systems, and you own the product definition, prioritization, pricing, packaging, and mechanisms that turn those systems into products customers buy, trust, and plan against. It is one of the most critical roles at Lambda. Compute, storage, and networking each ship as separate AI Cloud primitives. However, we view it as important to have a single leader that can bring them together in a seamless experience for training runs and/or inference that touch all three services at once. Hardware is what makes those decisions durable. GPU platform generations turn over quickly, each one changes power, cooling, density, and what a customer can train, and customers commit to platforms on multi-year contracts before those platforms arrive, so the decisions you make now set what Lambda can sell for years. Lambda works closely with NVIDIA as a partner and investor, and this role leads the product integration of that partnership or makes sure someone on the team does. You will partner with their development efforts, bringing Lambda's operating experience and customer requirements to the technologies they are building and helping test them at scale, and you will make sure Lambda adopts that technology in the right places, with the right customer commitments, and with the product definition needed for the company to sell and support it. This is a player and coach role. You will hire, level, and develop product managers who can take genuinely ambiguous problems and turn them into definition the rest of the company plans against, you will set the standard for how product work is written and reviewed here, and you will build the bench that grows into the next generation of product leaders at Lambda. You will also stay close enough to the work to drive the unified experience across compute, storage, and networking yourself. 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 compute, networking, storage, or hardware platform experience at a cloud computing platform is highly desired. If you want a role where you can change the shape of how AI is done in the cloud and build a team that turns hardware into products customers can bet their work on, we would like to hear from you.   What You'll Do - Own the Product Definition: Define compute, storage, and networking products for Lambda, including the customer promise, product boundaries, launch criteria, pricing, and packaging. - Set the Roadmap: Build and maintain the roadmap for the products that sit underneath On-Demand GPU Instances and 1-Click Clusters, and make the tradeoffs clear enough that engineering, sales, finance, and support can plan against them. - Connect the Domains: Hold compute, storage, and networking together as one customer experience, so product decisions reflect how distributed training and inference workloads actually run. - Lead Pricing and Packaging: Own pricing and packaging decisions for compute, storage, and networking, including how customers buy capacity, compare options, and make multi-year commitments. - Drive Hardware Productization: Turn new GPU platform generations into products Lambda can sell and support, including capacity definition, customer requirements, launch sequencing, and adoption plans. - Partner with NVIDIA: Lead product integration with NVIDIA or assign clear ownership on your team, partnering with their development efforts and testing and adopting new technologies in the right Lambda products. - Build Operating Mechanisms: Create the planning, review, launch, and feedback mechanisms that let Lambda make product decisions across engineering, sales, finance, support, and operations. - Develop Product Leaders: Hire, coach, and manage product managers who can work through ambiguous technical and commercial problems, write clear product definition, and move the company toward a shared outcome. You - Have 10+ years of product management experience, including managing product managers. - Have built your career in cloud computing, and have worked directly on at least two of compute, networking, and storage, ideally all three, with enough knowledge of the third to make decisions in it. - Can reason about performance, durability, cost, and customer impact with engineering leaders across all three domains. - Have owned product strategy, roadmap, pricing, and packaging for infrastructure products, at a scope where your decisions set company direction. - Have worked on products where hardware constraints, supply timing, or platform transitions shaped the roadmap. - Have managed senior product managers and raised the quality of their written product definition, judgment, and execution. - Able to define iterative plans that move an organization from the current state towards the desired outcome - Can translate ambiguous customer, technical, and commercial inputs into product definition that multiple teams can execute. - Are comfortable making tradeoffs across engineering complexity, customer commitments, margin, and delivery timing. - Communicate plainly, write well, and make decisions easier for people who do not all share the same context. Nice to Have - Experience with GPU cloud, AI infrastructure, distributed training, or large-scale inference products. - Experience with NVIDIA GPU platforms, InfiniBand networking, NVLink, or high-performance storage systems. - Experience building products for both self-serve developers and committed enterprise customers. - Experience working directly with strategic technology partners on product integration and adoption. - Experience with products that include usage-based pricing, reserved capacity, or multi-year customer commitments. 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 - W…