Senior Director, AI Product Management - Data Center
- Compensation
- Not disclosed
- Location
- San Diego, California, United States of America
- Work setup
- Onsite
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 10+ years
- Category
- Not specified
- Posted
Skills
Nice to have
- Ph.D. in Computer Architecture, Data Center Systems, Machine Learning Systems or related field.
- Direct experience with AI frameworks (TensorFlow, PyTorch), compilers and optimization toolchains.
- Familiarity with emerging data center trends such as disaggregated architectures, DPUs, or AI inference at the edge.
- Patent filings or technical publications in AI accelerator design, high-performance interconnects, rack-scale architectures or thermal/power management.
- 12+ years of product management experience, with at least 5 years focused on data center or AI infrastructure.
- Deep system-level knowledge of AI accelerators, CPU/GPU architectures, interconnect fabrics (PCIe, CXL, UAL), memory hierarchies, storage subsystems, and rack-level system design (power delivery, cool
- Demonstrated success defining and launching complex silicon-plus-software AI products and rack-scale solutions in collaboration with cross-functional development teams.
- Proven ability to engage with C-level executives and engineering leads at hyperscale cloud providers or tier-1 enterprise customers.
- Strong analytical skills, comfortable with financial modeling, market sizing, and competitive benchmarking.
- Excellent communication and storytelling abilities—able to translate technical detail into clear business impact.
- Track record of leading and mentoring product management teams, fostering career growth and cross-functional collaboration
Full description
##
Company:
Qualcomm Technologies, Inc.
Job Area:
Operations Group, Operations Group > Product Management
General Summary:
Join Qualcomm’s rapidly expanding Data Center Business Unit as a Director of Product Management, where you will shape the future of AI-driven data center solutions. You’ll lead cross-functional teams to deliver end-to-end system-level innovations—from custom AI accelerators to full-stack software and rack-scale systems—driving performance, efficiency, and scale for hyperscale and enterprise customers.
Key Responsibilities:
- Define and execute the product strategy and roadmap for AI-centric data center platforms and rack-level systems, including compute nodes, interconnect fabrics, power delivery, and cooling subsystems.
- Lead market analysis to identify AI workloads and emerging system-level trends (e.g., large language models, inference at scale, rack-scale orchestration).
- Collaborate with silicon architects, systems engineers, firmware and software teams to translate market and customer needs into detailed product requirements and rack-level integration specifications.
- Engage directly with hyperscale cloud providers, enterprise customers and strategic partners to gather feedback, co-develop proofs of concept, and drive early deployments of rack-scale AI clusters.
- Partner with marketing and sales leadership to craft compelling value propositions, competitive positioning, launch plans and go-to-market collateral.
- Mentor and grow a high-performing team of product managers, fostering a culture of innovation, customer obsession, and rigorous decision-making. T
- rack product performance post-launch—covering system-level metrics like power efficiency, thermal headroom, and network utilization—iterating on features, pricing, and lifecycle management to maximize ROI and market share
While there is a strong preference for this position to be based in San Diego, remote work can be considered for the right candidate.
Minimum Qualifications:
- Bachelor's degree in Engineering, Information Systems, Computer Science, Humanities, or related field.
- 10+ years of Product Management or related work experience.
Preferred Qualifications:
- Ph.D. in Computer Architecture, Data Center Systems, Machine Learning Systems or related field.
- Direct experience with AI frameworks (TensorFlow, PyTorch), compilers and optimization toolchains.
- Familiarity with emerging data center trends such as disaggregated architectures, DPUs, or AI inference at the edge.