AI SoC Security Architect

Majestic LabsLos Altos, CA

About The Position

Majestic-Labs is a leader in accelerated computing, driving innovation across industries with groundbreaking technologies in AI, graphics, and high-performance computing.

Requirements

  • BSc, MS, or PhD in Electrical Engineering, Computer Science, Computer Engineering, or equivalent experience.
  • 10+ years of proven track record in hardware security architecture, silicon design, or embedded security engineering.
  • Deep, practical understanding of "Security-by-Design" principles, privilege isolation, and Confidential Computing concepts.
  • Strong programming and debugging fundamentals in C/C++, Python, and assembly (e.g., ARM) with hands-on experience in low-level firmware and embedded systems.
  • A proven track record of leading complex technical features across diverse, cross-functional teams, backed by excellent communication skills.

Nice To Haves

  • Direct experience with Linux security primitives, secure hypervisors, or microkernel architectures.
  • Background in high-performance networking security (RDMA, TCP/IP, TLS/IPSec)
  • Experience mitigating AI-specific hardware threats (e.g., side-channel analysis, fault injection).

Responsibilities

  • Research, design, and deliver hardware-and-software security architectures for our next-generation AI Inference Systems, ensuring alignment with global security standards.
  • Own the microarchitectural definition, validation, and rollout of the SoC Hardware Root of Trust (RoT) and secure boot processes.
  • Apply advanced hardware primitives to implement secure software compartmentalization, isolating critical AI assets and model IPs from multi-tenant threats.
  • Collaborate directly with software and research teams to embed secure firmware, model-protection mechanisms, and open-source security frameworks into the silicon platform.
  • Build and execute data-driven threat models to identify, validate, and mitigate hardware and low-level firmware vulnerabilities.
  • Lead security feature implementation from conceptual modeling and emulation through to customer deployment and threat resolution.
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