AI Infrastructure Operations, Demand Planning

Anthropics mission is to create reliable interpretable and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers engineers policy experts and business leaders working together to build beneficial AI systems.

Anthropic runs one of the largest and fastest-growing infrastructure fleets in the industry across multiple accelerator families CPU families clouds neoclouds and on-prem sites. Capacity Engineering owns the data tooling and systems that let Anthropic plan measure and maximize utilization of that fleet: 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. This role sits in the Planning pillar on the Demand Planning team and works daily with research engineering pretraining inference compute supply finance and external vendors.

You own the tranches. The job has two halves that feed each other. Upstream you take the Demand Planning forecast and turn it into per-tranche requirements shape interconnect region supporting resources date and carry those into sourcing negotiations and data center build reviews so we contract for capacity we can actually use when we need it. Downstream you own the integrated schedule and system of record for every tranche in flight from contracted through reserved ingested in-cluster healthy and occupied and you drive the owners of each hop to their dates. Every slip you see downstream becomes a contract-language fix an automation or a correction fed back to the forecast.

• Turn the forecast into per-tranche requirements. Take the Demand Planning forecast plus direct input from research pretraining and inference planners and convert it into concrete accelerator interconnect region supporting-resource and date requirements for each tranche. Represent those in sourcing negotiations and data center build reviews including which contractual terms actually move delivery dates.
• Qualify tranches for deliverability before signature. The Capacity Planner signs fit-to-forecast; you sign whether the shape can land schedulable healthy and instrumented in that region on that date with storage egress identity in place.
• Close the delivery loop. Track forecast-versus-delivered on shape region and timing for every tranche; publish the variance; and feed it back to Demand Planning and into the next contract.
• Own the bring-up system of record. Define the canonical contract-to-occupied state machine with explicit entry and exit criteria per stage and make it a first-class object in the capacity data layer so every downstream tool sees in-flight capacity not only what has landed.
• Run a portfolio of bring-ups in parallel new cloud regions on-prem sites neocloud blocks with one integrated schedule spanning provider milestones cluster creation network turn-up storage readiness health burn-in and first-workload landing.
• Drive readiness automation: All capacity systems are fully integrated for all new capacity from contracted through ingested automated and scaled.
• Instrument and publish the numbers that matter time-to-occupied and paid-idle dollars per tranche with executive-level reporting on status tradeoffs and risk across the portfolio.

• Significant experience delivering large-scale infrastructure cloud regions accelerator clusters HPC systems or bare-metal fleets at multi-region scale or 10k accelerators (or CPU/storage equivalent).
• Technical range from through cluster orchestration and node health up to the telemetry and planning tables on top enough to debug where they disagree rather than route it.
• SQL and enough Python to answer your own questions and build your own reporting.
• A degree in a technical field or an equivalent engineering track record.

• Reserved-capacity onboarding private offers or capacity commitments with cloud or neocloud providers.
• Enough demand-planning exposure to challenge a forecast translate it into per-tranche requirements and feed delivery variance back into it.
• Data center or colocation delivery: power and space planning network turn-up site acceptance vendor management.
• Accelerator health and burn-in collective-communications sanity testing or fleet-health SLOs and a rigorous definition of healthy.
• Systems of record or lifecycle services for infrastructure assets.
• Onboarding a new hardware generation into an existing scheduler and observability stack.

Minimum education: Bachelors degree or an equivalent combination of education training and/or experience

Required field of study:A field relevant to the role as demonstrated through coursework training or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently we expect all staff to be in one of our offices at least 25% of the time. However some roles may require more time in our offices.

Visa sponsorship:We do sponsor visas! However we arent able to successfully sponsor visas for every role and every candidate. But if we make you an offer we will make every reasonable effort to get you a visa and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy so we urge you not to exclude yourself prematurely and to submit an application if youre interested in this work. We think AI systems like the ones were building have enormous social and ethical implications. We think this makes representation even more important and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams remember that Anthropic recruiters only contact you some cases we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money fees or banking information before your first day. If youre ever unsure about a communication dont click any linksvisit for confirmed position openings.

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact advancing our long-term goals of steerable trustworthy AI rather than work on smaller and more specific puzzles. We view AI research as an empirical science which has as much in common with physics and biology as with traditional efforts in computer science. Were an extremely collaborative group and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic including: GPT-3 Circuit-Based Interpretability Multimodal Neurons Scaling Laws AI & Compute Concrete Problems in AI Safety and Learning from Human Preferences.

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits optional equity donation matching generous vacation and parental leave flexible working hours and a lovely office space in which to collaborate with colleagues. Guidance on Candidates AI Usage:Learn aboutour policy for using AI in our application process.