Director, AI Product Management - Data Center Business Unit

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 Bachelor's degree in Engineering, Information Systems, Computer Science, Humanities, or related field. 8+ years of Product Management or related work experience. 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, cooling, cabling, rack orchestration). 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