Senior Product Manager (AI Infrastructure & GPU)

Do you love building the foundational capabilities that power cloud computing?

Are you looking to bridge the gap between deep technical architecture and product strategy?

Come join our Cloud Technology Group!

This team is revolutionizing Akamai’s cloud into a global leader for advanced computing. It involves launching GPU instances, clusters, and AI infrastructure products. These solutions empower enterprises, developers, and researchers to train models, perform inference, and address complex computational challenges. The role requires expertise in GPU technologies, innovative product strategies, and operational precision within a dynamic, results-driven environment.

Partner with the best

As a Senior Product Manager for GPU Products, you will bring technical expertise, creativity, and focus for impactful outcomes.

As a Senior Product Manager, you will be responsible for:

• Defining product strategy and roadmap for GPU instances, clusters, and services, aligning positioning and requirements to customer and market needs.

• Managing the entire product lifecycle, from planning to end-of-life, while creating detailed business analyses and financial models for support.

• Developing and executing go-to-market strategies, messaging, and launch plans in partnership with marketing, sales, and solutions engineering.

• Collaborating with ecosystem partners, aligning their roadmap and platform integration with Akamai’s product objectives and technical needs.

• Translating AI, HPC, and graphics workload needs into specifications, performance goals, and architectures to enable design success and customer engagement.

• Overseeing GPU infrastructure lifecycle components, utilizing data-driven decisions on investments from platform evolution to implementing product End-of-Life as needed.

• Representing various user objectives while identifying enhancements for proactive monitoring, support processes, escalation workflows, and both planned and unplanned maintenance of Nvidia GPU clusters.

• Have 12 years of relevant experience and a Bachelor’s degree in Computer Science, Engineering, or its equivalent

• Have maintained a customer-first focus even when the customers are internal engineers and data scientists, prioritizing automation, usability, and low-friction integration for GPU workloads.

• Demonstrate expertise in GPU architectures, CUDA ecosystem, and accelerated computing plat