AI Infrastructure Operations, Demand Planning
- Salary
- $320,000 - $405,000
- Level
- Mid
- Visa
- Sponsors visas
Not stated in the posting: work type.
Open. First seen 20 September 2026.
What this role asks for
Particular to this role
SQL
Rare in Anthropic's other 299 open postings.
68% of this description is written for the role. The rest is Anthropic's standard text, folded away below.
Read against Anthropic's other open postings on this site.
The team: Software Engineering - Infrastructure HIRES STEADILY
This role is one of 44 open in Software Engineering - Infrastructure. 6 were posted in the last 30 days and the oldest in May: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
AWS (29 of 44), Python (29 of 44), GCP (28 of 44), Kubernetes (27 of 44), Rust (24 of 44), Azure (18 of 44), Golang (18 of 44)
OTHER ROLES ON THIS TEAM
- Principal Engineer Capacity/Compute posted Oct 18
- Senior+ Software Engineer, Legal Tech posted Sep 29
- Staff + Sr. Software Engineer, Cloud Inference posted Sep 28
- Staff + Sr. Software Engineer, Cloud Inference Launch Engineering posted Sep 28
- Staff + Sr. Software Engineer, Scaling posted Sep 28
- Engineering Manager, Data Infrastructure posted Sep 22
- Staff+ Software Engineer, Storage + Transfer posted Sep 18
- Senior Engineering Manager, Capacity Engineering posted Sep 11
- Software Engineer, Observability & Profiling posted Sep 2
- Engineering Manager, Inference Infrastructure posted Sep 1
- Engineering Manager, Scheduler and Fleet Efficiency posted Sep 1
- Staff + Senior Software Engineer, Inference posted Aug 17
- Staff Software Engineer, Infrastructure (Distributed Systems) posted Aug 12
- Staff+ Software Engineer, Privacy posted Aug 7
- Staff+ Software Engineer, Capacity Engineering posted Jul 14
- Engineering Manager, Agent Runtime Platform posted Jul 9
- Staff Engineer, Datacenter Server Lifecycle posted Jul 9
- Staff+ Software Engineer, Databases posted Jul 7
- Staff+ Software Engineer, Caching posted Jul 7
- Staff+ Software Engineer, Experimentation posted Jul 2
- Staff+ Software Engineer, Developer Acceleration posted Jul 2
- Staff + Senior Software Engineer, Inference Deployment posted Jun 29
- Staff+ Software Engineer, Inference Velocity posted Jun 12
- Staff + Senior Software Engineer, Inference Infrastructure posted Jun 8
- Staff Software Engineer, Node Infra posted May 7
- Staff Software Engineer, Kubernetes Platform posted May 7
- Staff Infrastructure Engineer, Cluster Infrastructure posted May 7
- Staff+ Software Engineer, Kubernetes Platform posted May 6
- Staff+ Infrastructure Engineer, Cluster Infrastructure posted Apr 30
- Staff+ Software Engineer, Node Infra posted Apr 28
- Staff Engineer, Datacenter Server Lifecycle posted Mar 11
- Staff Software Engineer, Inference posted Mar 11
- Staff+ Software Engineer, Observability posted Mar 3
- Staff Software Engineer, Continuous Integration posted Feb 13
- Staff+ Software Engineer, Data Infrastructure posted Feb 13
- Staff+ Software Engineer, Developer Productivity posted Feb 13
- Staff Software Engineer, AI Reliability posted Feb 7
- Staff Software Engineer, AI Reliability Engineering posted Feb 5
- Staff Software Engineer, AI Reliability Engineering posted Feb 3
- Staff Software Engineer, Inference posted Feb 2
- Staff+ Software Engineer, Claude App Infrastructure posted Jan 13
- Staff+ Software Engineer, Infrastructure (Distributed Systems) posted Oct 29
- Senior Software Engineer, Inference posted May 20
From the team and dates on Anthropic's own job board.
About the role
Anthropic's standard text
About Anthropic
Anthropic’s 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.
About the Role
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.
What you'll do
- 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.
What you bring
- 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.
Preferred
- 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.
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000—$405,000 USD
Logistics
Minimum education: Bachelor’s 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 aren't 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.
Anthropic's standard text
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 you're interested in this work.
We think AI systems like the ones we're 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 from @anthropic.com email addresses. In 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 you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How we're different
Anthropic's standard text
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. We're 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.
Come work with us!
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 about our policy for using AI in our application process.
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