Group Product Manager - AI Infrastructure

Lambda•San Francisco, CA

3d•Onsite

About The Position

We are seeking an experienced Group Product Manager (GPM) to lead our product management team in building the next generation of AI infrastructure services. This role will oversee a portfolio of products that power large-scale AI workloads—including GPU clusters, cloud computing environments, and advanced storage and networking solutions. The GPM will set product vision and strategy, manage and mentor a team of Product Managers, and work cross-functionally to deliver best-in-class infrastructure products that meet the demanding needs of AI researchers, developers, and enterprises.

Requirements

10+ years of product management experience, with at least 3+ years managing PMs.
Bring deep expertise in AI infrastructure, cloud computing, or high-performance computing (HPC).
Understand GPUs, distributed systems, and cloud platforms at a technical level.
Possess strong leadership skills and a track record of building and scaling PM teams.
Can craft and communicate product strategy across a portfolio and balance near-term wins with long-term bets.
Thrive in cross-functional environments and excel at stakeholder alignment and communication.

Nice To Haves

Experience with AI/ML workloads such as model training, inference, and fine-tuning.
Familiarity with hyperscaler or specialized AI cloud environments.
Advanced technical degree (e.g., Computer Science) and/or MBA.

Responsibilities

Lead, mentor, and develop a high-performing team of Product Managers (ranging from PM to Principal PM).
Define and own the long-term product vision and strategy for Lambda’s AI infrastructure offerings—including compute, storage, and networking.
Oversee a portfolio of infrastructure products, including GPU clusters, high-performance storage, orchestration systems, and more.
Ensure cross-product cohesion to deliver a seamless and integrated cloud experience.
Collaborate with engineering, operations, and GTM teams to deliver performant, cost-effective, and scalable solutions.
Engage deeply with AI-first customers to translate real-world workload needs (training, fine-tuning, inference) into clear product specifications.
Track and anticipate industry trends in cloud infrastructure, AI workload optimization, and distributed systems.
Drive product excellence and ensure success metrics (e.g., adoption, utilization, customer satisfaction) are met or exceeded.