Responsibilities
- Own the multi-year product roadmap, aligning with technology inflection points such as AI Storage Solutions, and emerging AI Storage Solutions architectures.
- Translate market dynamics, customer signals, and competitive insights into product requirements (MRD/PRD).
- Lead deep technical engagements with hyperscalers and chipmakers (e.g., NVIDIA, AMD), turning customer performance, latency, and capacity needs into engineering deliverables.
- Position product solutions for AI inference, KV-cache, and memory-centric architectures informed by industry trends, inference context memory, KV-tiering.
- Build business cases including TAM/SAM/SOM models, pricing strategies, investment requirements, and ROI modeling.
- Guide lifecycle execution from concept → development → through cross-functional program reviews (Stage Gate).
- Partner closely with ASIC, firmware, NAND, system, and quality teams to drive technical readiness and performance targets.
- Manage supplier relationships and work with supply chain to ensure cost, yield, and delivery success.
- Coordinate internal alignment with engineering, reliability, operations, and exec staff.
- Maintain a robust understanding of the semiconductor memory landscape—AI Storage Solutions competition, NAND-AI Storage Solutions, emerging AI architectures, and customer platform roadmaps.
Requirements
- Strong understanding of: 3D stacking / TSV Memory–accelerator integration (AI/ML GPU pipelines)
- Strong understanding of: Memory subsystem architecture and performance analysis
- Strong understanding of: AI Storage Solutions, NAND-based high-bandwidth architectures
