Staff Product Manager - Data Center AI Software

Qualcomm•San Diego, CA

6d•$179,200 - $268,800•Onsite

About The Position

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 and deployment tools, Kubernetes and cloud-native AI infrastructure, Model onboarding and validation workflows, Benchmarking and performance analysis tools, Developer experience and ecosystem integration. Engage directly with cloud service providers, enterprises, system integrators, and ISV partners. Gather requirements and translate customer needs into actionable product plans. Support proof-of-concepts, customer evaluations, and production deployment initiatives. Present product strategy and technical capabilities to executive stakeholders and customers. Monitor AI infrastructure trends and competitive offerings across NVIDIA, AMD, Intel, AWS, Google, and emerging AI accelerator providers. Evaluate emerging AI frameworks, open-source projects, and ecosystem technologies. This is an office based position located in San Diego, CA and is expected to comply with the company's onsite work policy.

Requirements

Bachelor's degree in Engineering, Information Systems, Computer Science, Humanities, or related field.
5+ years of Product Management or related work experience.

Nice To Haves

Bachelor's degree in Computer Science, Engineering, Electrical Engineering, or related technical field.
Master's degree or PhD in Computer Science, AI/ML, Electrical Engineering, or related field.
8+ years of product management, software engineering, technical marketing, or related experience.
5+ years of experience in AI/ML, cloud infrastructure, distributed systems, or data center technologies.
Strong understanding of Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI inference technologies.
Experience working with AI frameworks such as PyTorch, TensorFlow, vLLM, SGLang, Hugging Face, Ray, or equivalent technologies.
Familiarity with cloud-native technologies including Kubernetes, Docker, and distributed computing systems.
Experience defining product requirements and executing complex technical roadmaps.
Strong communication, leadership, and stakeholder management skills.
Experience with AI accelerator hardware, GPUs, NPUs, or custom silicon platforms.
Knowledge of LLM serving architectures, optimization techniques, quantization, and distributed inference.
Experience with AI benchmarking and performance analysis.
Familiarity with inference metrics such as TTFT, TPOT, throughput, latency, and scaling efficiency.
Experience working with hyperscale cloud providers and enterprise AI customers.
Background in open-source AI ecosystems and developer communities.
Demonstrated success launching enterprise software or AI infrastructure products.

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 and deployment tools, Kubernetes and cloud-native AI infrastructure, Model onboarding and validation workflows, Benchmarking and performance analysis tools, Developer experience and ecosystem integration.
Engage directly with cloud service providers, enterprises, system integrators, and ISV partners.
Gather requirements and translate customer needs into actionable product plans.
Support proof-of-concepts, customer evaluations, and production deployment initiatives.
Present product strategy and technical capabilities to executive stakeholders and customers.
Monitor AI infrastructure trends and competitive offerings across NVIDIA, AMD, Intel, AWS, Google, and emerging AI accelerator providers.
Evaluate emerging AI frameworks, open-source projects, and ecosystem technologies.