Continuous learning — stays current with evolving AI systems, inference runtimes, interconnects, memory technologies, and cloud infrastructure trends A strong candidate will have enough depth to reason from first principles, enough practical experience to understand implementation constraints, and enough leadership range to align research, architecture, software, and silicon teams around a coherent direction. Drive hardware-software co-design across compute, DPU/IPU, NIC, SoC fabric, and AI serving runtimes, ensuring that networking and data-movement capabilities are reflected in modern inference and training frameworks such as vLLM, SGLang, and others Architect AI-Scale Networking and Interconnect .