Staff PM: Data Center AI Software & Infra Strategy

Qualcomm; San Diego (CA); On-site; USD 179,200 - 268,800; Full time

Job summary

Qualcomm Technologies, Inc. is seeking a Staff Product Manager for Data Center AI Software in San Diego to lead the strategy and requirements for AI software stacks and related tooling.

You will own roadmaps, collaborate with cloud providers and customers, and drive deployment and validation workflows across large-scale AI infrastructure. The role emphasizes deep knowledge of Generative AI, LLMs, and AI inference, plus experience with Kubernetes, Docker, and open frameworks.

Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, Humanities, or related field.
• 5+ years of Product Management or related work experience.
• Strong understanding of Generative AI, Large Language Models (LLMs), and AI inference technologies.

Responsibilities

• Develop product requirements based on customer feedback, competitive analysis, industry trends, and business objectives.
• Own the strategy and requirements for AI software stacks including LLM optimization, Kubernetes and cloud-native AI infrastructure, model onboarding and validation workflows, benchmarking and performance analysis tools, and developer experience.
• Engage directly with cloud service providers, enterprises, system integrators, and ISV partners; gather requirements and translate customer needs into actionable product plans.
• Monitor AI infrastructure trends and competitive offerings across major players; evaluate emerging AI frameworks and ecosystem technologies.

Skills

Product Management

Generative AI

AI/ML

Cloud infrastructure

Stakeholder management

Education

Bachelor's degree (Engineering / CS / related)

Tools

Kubernetes

Docker

Job description

Qualcomm Technologies, Inc. is seeking a Staff Product Manager for Data Center AI Software in San Diego to lead the strategy and requirements for AI software stacks and related tooling.

You will own roadmaps, collaborate with cloud providers and customers, and drive deployment and validation workflows across large-scale AI infrastructure. The role emphasizes deep knowledge of Generative AI, LLMs, and AI inference, plus experience with Kubernetes, Docker, and open frameworks.