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Anthropic is hiring senior hardware systems architects to own the system-level architecture of compute infrastructure for frontier AI models. The Hardware Systems team is responsible for designing and deploying some of the largest and most diverse accelerator fleets in the world, spanning from package boundaries through boards, racks, interconnect, power, cooling, and datacenter interfaces.
In this role, you will set hardware architecture direction, write specifications that partners and internal teams build against, and own validation and qualification strategies. You'll work across the full hardware stack—power, cooling, mechanical, interconnect, signal integrity, data and control planes, system management, and reliability—applied to networking, compute, storage, and accelerator systems.
Key responsibilities include: owning system architecture pathfinding from concept through deployment; writing high-level requirements and specifications for boards, interfaces, and racks; reviewing vendor designs and making build/buy/co-design decisions; driving interconnect and networking architecture for scale-up and scale-out fabrics; architecting board, chassis, and system-level designs with partners; developing performance simulations and hardware models; defining validation and qualification strategies; partnering with ML performance and infrastructure teams; and helping shape how hardware engineering operates at Anthropic through AI-assisted design and review approaches.
You'll collaborate closely with ML performance, infrastructure software, supply chain, and datacenter teams, as well as directly with hardware vendors and partners. Claude will be a genuine collaborator on this team, and you're expected to push on what AI-assisted hardware design and review can achieve.
Minimum qualifications include deep hands-on expertise in at least one core hardware-systems domain (interconnect, power, thermal) for large-scale compute or networking; experience owning hardware system architecture at scale and authoring specifications; experience taking hardware from architecture through production deployment; vendor management and design review experience; ability to reason about trade-offs across adjacent hardware domains; a track record of technical leadership; comfort with high autonomy in fast-moving environments; and strong written communication skills.
Preferred qualifications include 8+ years in hardware systems architecture for hyperscale, HPC, AI/ML, or high-end networking; experience with AI accelerator systems and their fabrics; familiarity with chip-package-system interfaces and co-design; experience establishing new engineering functions or practices; comfort with AI tools in engineering workflows; and a degree in EE, CE, ME, CS, or related field.
