Platform Hardware Security

Anthropic Anthropic · AI Frontier · San Francisco, CA · Security

This role focuses on designing and implementing security architectures for bare-metal infrastructure, including firmware, bootloaders, operating systems, and attestation systems, to ensure the integrity of AI training infrastructure. The engineer will work on low-level systems security, balancing security with the performance demands of AI model training.

What you'd actually do

  1. Design and implement secure boot chains from firmware through OS initialization for diverse hardware platforms (CPUs, BMCs, switches, peripherals, and embedded microcontrollers)
  2. Architect attestation systems that provide cryptographic proof of system state from hardware root of trust through application layer
  3. Develop measured boot implementations and runtime integrity monitoring
  4. Create reference architectures and security requirements for bare-metal deployments
  5. Integrate security controls with infrastructure teams without impacting training performance

Skills

Required

  • secure boot
  • measured boot
  • attestation technologies (TPM, Intel TXT, AMD SEV, ARM TrustZone)
  • cryptographic protocols
  • hardware security modules
  • UEFI/BIOS or embedded firmware security
  • bootloader hardening
  • chain of trust implementation
  • low-level programming (C, Rust, Assembly)
  • systems programming
  • firmware vulnerability assessment
  • threat modeling
  • security architectures for complex, distributed systems
  • supply chain security
  • hardware and software boundaries
  • NIST firmware security guidelines
  • hardware security frameworks

Nice to have

  • confidential computing technologies
  • hardware-based TEEs
  • SLSA framework
  • software supply chain security standards
  • securing large-scale HPC or cloud infrastructure
  • open-source security projects (coreboot, CHIPSEC, etc.)
  • formal verification
  • security proof techniques
  • silicon root of trust implementations
  • foundational technical designs
  • operational leadership
  • vendor collaboration
  • AI/ML infrastructure security

What the JD emphasized

  • security architectures for bare-metal infrastructure
  • firmware, bootloaders, operating systems, and attestation systems
  • integrity of our infrastructure from the ground up
  • security requirements with the performance demands of training AI models