Infrastructure Capacity Planner, Demand Planning

Anthropic•San Francisco, CA

18h•$320,000 - $405,000•Hybrid

About The Position

Anthropic's infrastructure fleet spans a growing set of clouds, neoclouds, and on-prem sites. Every part of it is expanding rapidly. Capacity Engineering is the team that connects every stage of that growth, from capacity planning to supply management to capacity delivery to utilization. We partner on supply deals, wire telemetry from day zero, own the canonical capacity data layer, and build the planning and enforcement tools every research and product team relies on. As an Infrastructure Capacity Planner on the Demand Planning team, you'll own the medium-range demand forecast for every resource class we consume: accelerators, CPU, storage, network, and managed services. Your forecast will support sourcing and purchasing, prioritization, efficiency targets, and workload optimization.

Requirements

Have done capacity, demand, or supply planning for large-scale technical infrastructure (cloud, HPC, hyperscale, or a large internal platform) and can articulate the difference between a forecast, a plan, and an allocation.
Build the model yourself rather than specifying it for someone else: SQL against a warehouse, Python/pandas or a proper forecasting/optimization stack.
Understand data-center resource classes well to know why storage and egress don't forecast like GPUs, and why a contract's headline chip count is rarely the binding constraint.
Prefer simple, inspectable models to clever opaque ones, and instrument your own forecast error.

Nice To Haves

Direct experience with cloud or neocloud providers on reserved-capacity onboarding, private offers, or capacity commitments.
Demand planning or forecasting experience for accelerator fleets, including translating research or product roadmaps into resource requirements.
Data center or colocation delivery experience: power and space planning, network turn-up, site acceptance criteria, and vendor management.
Experience with accelerator health and burn-in, collective-communications sanity testing, or fleet-health SLOs, and the ability to define healthy rigorously.
Experience building lifecycle or state-machine services, or systems of record for infrastructure assets.
Experience onboarding a new hardware generation into an existing scheduler and observability stack.

Responsibilities

Build and own the medium-range multi-resource demand forecast: accelerators by chip/interconnect class, CPU by shape, storage by tier and access pattern, egress by path, managed services by SKU — driven by model roadmap, RL/inference growth, eval volume, and retention policy rather than trend lines.
Run the plan-vs-reality loop. Diff planned allocations against observed fleet occupancy weekly, surface unrecorded trades and stale allocations, and drive variance toward zero with our planning-tools and data teams.
Qualify each incoming capacity tranche against the forecast before signature: right shape, region, quarter, and supporting-resource envelope (storage, egress, CPU).
Partner with Finance and cost-efficiency teams to turn the forecast into core drivers covering the large majority (≥80%) of non-accelerator spend, and to aim savings work where waste will appear next.