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Lambda is a leader in AI cloud infrastructure serving tens of thousands of customers, from AI researchers to enterprises and hyperscalers. As VP of Product Marketing, you will build the programs that establish Lambda as the most credible name among AI cloud providers, defining how products and infrastructure are positioned, launched, and understood in the market.
Key responsibilities include leading and developing the PMM team to build a vision of rigorous thinking and sharp execution; driving customer stories that illustrate Lambda's capabilities and competitive advantages; building technical credibility through benchmarks, white papers, and performance analyses; marketing data center and infrastructure assets to support multi-billion-dollar deals; owning product positioning and messaging across Lambda's full portfolio; driving go-to-market strategy for product launches end-to-end; establishing a competitive intelligence program for the cloud AI landscape; and defining PMM KPIs to measure pipeline influence, win rates, and product adoption.
You bring 10+ years of product marketing experience at B2B cloud, data center, cloud infrastructure, or AI companies, with demonstrated impact on pipeline, win rates, or market perception. Experience at a specialized GPU cloud provider or hyperscaler's AI infrastructure division is strongly preferred. You understand the difference between marketing to ML engineers versus enterprise infrastructure buyers, and you've built or significantly grown a PMM function before. You think in programs rather than projects, designing repeatable systems that compound over time. You balance strategic thinking with hands-on execution, can write positioning briefs and help TPMMs close case studies, and have launched complex technical products with rigorous go-to-market processes. You lead with data, track outcomes, and use information to make better decisions. Direct experience marketing data center capacity, colocation services, or large-scale GPU clusters is essential, as is in-depth understanding of training, inference, AI data centers, and infrastructure.
The role requires presence in the San Francisco or San Jose office 4 days per week, with Tuesday designated as the work-from-home day.
