Anthropic Technical Program Manager role at Anthropic owning cross-functional billing programs. Responsible for driving billing platform foundations and commercialization readiness.
Responsibilities
Anthropic is building custom silicon for Claude. The hardware our models run on is one of the most direct levers we have on capability, cost, and reliability — and we've decided to take design authority over it ourselves.
We're looking for a Technical Program Manager to own end-to-end execution of our silicon, from architecture definition through tapeout, first-silicon bring-up, and production ramp. You'll be working alongside a small group of domain experts across front-end design, verification, physical design, DFT, analog/mixed-signal, foundry, and packaging. There is no process to inherit — you'll build the execution machinery this program runs on.
This is a partner-heavy program by design. You'll drive a portfolio of external engagements — ASIC design services, IP vendors, foundry, and OSAT. You should have shipped chips before, know what a realistic silicon schedule looks like and its failure modes, and be comfortable making consequential program calls without a large organization behind you. And because this is Anthropic, you'll have Claude as a collaborator — we expect the TPMs on this team to push hard on what AI-assisted program management can look like.
Own the integrated silicon program plan — architecture closure, RTL freeze, DV milestones, IP delivery, PD closure, DFT, tapeout, and post-silicon bring-up.
Drive external partner execution across ASIC design partners, IP vendors, foundry, and packaging/test.
Run technology and IP selection as a program: track candidate vendors and options, drive evaluations to a decision, and land the build / buy / license calls with engineering leadership.
Build the execution mechanisms a silicon team needs — milestone definitions, risk and dependency tracking, design reviews, release management, exec reporting — and keep them lightweight enough that engineers actually use them.
Manage the interface between silicon and its consumers: hardware systems for package/board/bring-up, and inference/kernels/compiler teams for hardware-software co-design, so trade-offs land as coordinated decisions rather than late surprises.
Own the post-silicon program — bring-up planning, ATE/test handoff, sample distribution, validation, and the path to production readiness.
Develop and share AI-assisted approaches to program management — schedule and dependency modeling, spec and milestone consistency checking, partner-deliverable tracking, status synthesis.
Qualification
Strong written communication — plansExperience on ML acceleratorsBS/MS in EE
Required
8+ years in silicon/SoC program management, chip lead, or an equivalent role that owned a chip schedule end to end.
Direct ownership of at least one program that taped out and reached production, with milestones you can speak to in detail — including where it slipped and what you did about it.
Working technical fluency across the silicon lifecycle — front-end, DV, PD, DFT, foundry, packaging.
Experience running external silicon partners — ASIC houses, IP vendors, foundry, or OSAT — including SOW scoping, delivery tracking, and escalation.
Track record of building program mechanisms from scratch on an ambiguous, fast-moving effort.
Strong written communication — plans, reviews, and exec updates that many teams depend on.
Comfort operating with high autonomy and limited process on a highly dynamic program.
Preferred
Experience on ML accelerators, high-performance compute, networking, or other large, high-bandwidth SoCs at advanced process nodes.
Experience on a first-generation or early silicon program, including standing up flows, methodology, or vendor relationships from nothing.
Experience with both partner-executed and fully in-house programs, and a view on the trade-offs between them.
Prior hands-on engineering background in one or more silicon domains (design, DV, PD, DFT, or SI/PI).
Familiarity with the chip-package-system interface and co-design with a hardware systems team.
Experience with hardware-software co-design programs — working directly with compiler, kernel, or runtime teams.
Practical experience using AI tools in your own workflow, and clear ideas about where they help and where they don't.
BS/MS in EE, CE, CS, or a related field, or equivalent experience.
