Design Architecture, Principal Engineer

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Job Description
HBM Design Architecture — Principal Engineer

Role Overview

We are seeking a highly motivated HBM Design Architecture Engineer (Principal Engineer) to drive exploration and definition of next‑generation AI memory and system environments. In this role, you will analyze emerging infrastructure trends, build performance models, and develop/extend tooling that informs HBM architecture decisions and system‑level trade‑offs.You will work closely with architects and senior engineers across DTPCO, Design, and Product/System teams to translate AI workload requirements into actionable memory subsystem and architectural intercept strategies.

Key Responsibilities

You will own and contribute to projects such as:

Research and synthesize emerging trends in compute, networking, and storage infrastructure to anticipate how future AI systems will evolve.

Lead HBM architecture analysis by defining bandwidth/latency targets, identifying constraints, and translating workload and system data into actionable memory requirements.

Develop and maintain simulation frameworks to model AI cluster performance and memory subsystem behavior; validate models against internal and external benchmarks.

Build and apply first‑order performance models spanning HBM bandwidth/latency, GPU/CPU interactions, and memory hierarchy trade‑offs to guide architectural decisions.

Create and curate trend dashboards using CSP benchmarks and industry datasets; communicate insights, assumptions, and sensitivity analyses to stakeholders.

Partner across DTPCO, Design, and Product/System teams to define architectural intercept opportunities, align on requirements, and influence roadmaps for next‑generation AI systems.

Required Qualifications

Bachelor’s or Master’s degree in Electrical Engineering, Materials Science or related field (or equivalent practical experience).

Strong understanding of materials and technology challenges spanning hybrid computing systems

Experience with memory subsystem design (HBM, DDR, caches) and how memory behavior impacts AI/ML workloads and system bottlenecks.

Strong multi-disciplinary experience in Fab & Foundry space.

Preferred Skills

Exposure to electrical, materials challenges and advances in microelectronic manufacturing (compute, memory, interconnects).

Ability to turn research and model outputs into concise technical recommendations, including trade‑off discussions, risk/unknowns, and roadmap implications.

AI Relevant Job Responsibilities:

• Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements.

• Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.

• Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business