Responsibilities include defining product positioning and feature requirements, shaping future silicon and IP investment priorities, partnering with engineering and architecture teams to evaluate technology trade-offs, and aligning roadmap decisions with customer needs, competitive dynamics, platform reuse, cost, power, performance, schedule, and long-term business strategy. Bring AI silicon definition expertise, including understanding of LLM architectures, transformer-based models, generative AI workloads, memory and bandwidth requirements, accelerator partitioning across CPU, GPU, NPU, and external AI accelerator attach platforms, and software stack implications for on-device, hybrid, and externally accelerated AI experiences.