Principal Engineer, AI System Architect; Hardware

Principal Engineer, AI System Architect (Hardware)

San Jose, California, United States

Advancing the World's Technology Together

Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you'll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what's possible and powering the future.

We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We're dedicated to empowering people to be their true selves. Together, we're building a better tomorrow for our employees, customers, partners, and communities.

Job Title:

Principal Engineer, AI System Architect (Hardware)

The Architecture Research Lab (ARL) focuses on addressing fundamental system-level bottlenecks in modern AI, particularly in memory capacity/bandwidth and system-scale communication. By leveraging Samsung's world-class memory technologies, ARL explores and defines next-generation AI system architectures that deliver step-function improvements in performance, efficiency, and scalability. We are seeking a Principal AI System Architect who will play a Technical Lead role in bridging AI workloads, system architecture, and hardware design.

In this role, you will develop system-level performance models, drive architecture-level design decisions, and propose forward-looking AI system architectures that shape Samsung's long-term AI platform strategy.

Location:

Daily onsite presence at our San Jose office in alignment with our Flexible Work policy

What You'll Do

• Technically lead the architecture team with strong direction, shaping system-architecture strategy and advancing key innovations
• Conduct system-level architectural research for next-generation AI systems, spanning compute, memory, and interconnect/network subsystems.
• Develop and maintain analytical and simulation-based system modeling frameworks to evaluate AI workloads and identify performance, scalability, and efficiency bottlenecks at rack- and system-scale.
• Analyze representative and emerging system-level architectural research (e.g., LLMs, DLRMs, and future AI models) to derive architecture requirements and trade-offs across compute, memory, networking, and power.
• Drive architecture-level design decisions through quantitative modeling, design-space exploration, and performance/power projections.
• Perform comparative studies of alternative system architectures, reporting performance and performance-per-watt metrics to guide strategic technology choices.
• Collaborate closely with cross-functional teams in hardware architecture, memory, interconnect, and system engineering to align modeling insights with implementation realities.
• Communicate architectural insights and recommendations through clear technical presentations and documentation.
• Occasional domestic and international travel (