СШАStaff Integrated Capacity Planner
2 нед. назад
СШАLeadOnsite
This role owns the integrated planning system connecting strategy to execution at an AI infrastructure company.
Обязанности
- At , the Capacity Planning & Efficiency team operates at the critical intersection of all products, services, and underlying physical infrastructure. This role owns the integrated planning system itself - the connective tissue that turns long-range strategy into a committed, buildable, fundable plan. You will run the end-to-end planning rhythm across every resource class: GPU and accelerated AI fabrics, compute, storage (File, Object, and Block), network, and the data center power and space that gates all of it. You will own long-range planning, the integrated business planning cycle, allocation and constraints planning, the operating calendar, and the supply chain and financial commitments that flow out of them.
- This is a single pane of glass role. Where domain planners go deep on one resource, you go wide across all of them and arbitrate - reconciling demand signals against supply commitments, hardware lead times, site readiness, and capital and operating budgets into one defensible plan the company runs on. You will not own any single resource domain; you own the system that reconciles them all, and the calls that fall out of it when supply is short. You will partner directly with Finance to translate the capacity plan into demand capex and opex forecasts, and you will be the person leadership turns to when a constraint, a slip, or a demand surprise forces a re-plan. This role is uniquely positioned to maximize fleet utilization with company-wide impact, directly supporting 's mission to align the future of computing with environmental sustainability.
Требования
- Proven Integrated Planning Expertise: 8+ years in infrastructure capacity planning, IBP/S&OP, supply and demand planning, systems engineering, or technical program management, including end-to-end ownership of a recurring planning cycle. Strong candidates come from either deep infrastructure or formal planning backgrounds - we expect to teach the other half.
- Breadth Across Resource Classes: Technical fluency across compute, storage (File, Object, and Block), network, and accelerated computing, plus the power, space, and cooling constraints that govern deployment. Deep expertise in one domain is not required; holding your own with the people who have it is.
- Supply Chain Fluency: Practical experience with lead times, supplier allocation, buffer strategy, and converting a plan into committed purchase orders and delivered hardware.
- Financial Acumen: Comfort operating in capex and opex terms - building demand-driven capital forecasts and defending the numbers in front of Finance and leadership.
- Modeling Craft: Expert-level Excel or Google Sheets. You build models other people can inherit, audit, and run without you - clear structure, documented assumptions, versioned, and still trustworthy several quarters after they were built.
- Hyper-Growth Experience: Planning inside high-growth public cloud environments or massively distributed systems, where the plan changes and the rhythm still has to hold.
- Exceptional Influence & Communication: Structured narrative delivery, crisp documentation, and executive-grade presentations that turn a complex plan into a decision leadership can make in the room. You will run a planning cycle spanning five organizations without managing any of them, and escalate cleanly when alignment is not reachable.
- Education: Bachelor's or Master's degree in Computer Engineering, Computer Science, Operations Research, Industrial Engineering, Supply Chain, Mathematics, Data Science, or an equivalent technical field.
Будет плюсом
- Experience standing up an S&OP or integrated business planning function from scratch, including the cadence, data model, and decision forums.
- Experience building or defining foundational product requirements for custom in-house planning, provisioning, or capacity modeling software.
- Hands-on quantitative modeling skill - SQL, Python, or optimization and simulation methods applied to constrained allocation problems.
- Direct experience planning GPU clusters and accelerated AI computing fabrics at scale.
Условия
- Competitive compensation and equity packages
- Restricted Stock Units
- Paid time off, paid holidays & leave of absence programs
- Comprehensive health, dental & vision insurance
- Employer contributions to HSA account
- Paid parental leave
- Paid life insurance, short-term and long-term disability
- Professional development & tuition reimbursement
- Mental health & wellness support
- Commuter benefits (parking & transit)
- Cell phone stipend
- 401(k) Retirement plan with company match up to 4% of salary
- Volunteer time off
- Global travel insurance & emergency assistance
- Daily meals allowance
- Additional perks & programs specific to location
- Compensation will be paid in the range of up to $200,000-$240,000+ Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data.
Другое
- is on a mission to accelerate the abundance of energy and intelligence . As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join , you join a team that is building the future, faster.
- We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.
- We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.
- If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at .
- Long-Range Capacity Planning: Own the multi-year outlook across GPU, compute, storage, network, and the power and site energization schedules that gate all of it, and build the scenario models - demand cases, technology transitions, refresh and decommission waves - that inform where commits capital and builds next.
- Integrated Business Planning: Run the IBP/S&OP cycle end to end - demand review, supply review, reconciliation, and the executive decision forum. Maintain both the unconstrained demand signal and the constrained committed plan; the gap between them is how sizes what it is leaving on the table.
- Constraints & Bottleneck Planning: Maintain a live model of what is actually binding - silicon allocation, supplier lead times, power energization, rack and network availability, deployment labor - quantify the impact of each, and drive every mitigation to a decision.
- Allocation & Arbitration: Own the framework that decides which demand gets which capacity when supply is short - prioritization rules, trade-off analysis, and a clean escalation path when the call has to go to leadership.
- Plan of Record & Operating Calendar: Design and run the planning calendar that synchronizes Cloud Engineering, Supply Chain, Data Center Operations, Product, and Finance. Govern the plan of record - commitment time fences, what is frozen versus still movable, and what triggers a re-plan.
- Demand & Bookings Translation: Convert contracted commitments, backlog, ramp schedules, and on-demand growth into resource-level forecasts, including the attach ratios that link GPU capacity to storage, network, and compute. Manage forecast accuracy and bias as owned metrics.
- Supply Chain Integration: Translate the plan into supplier commitments, purchase timing, and buffer strategy, navigating global lead times and allocation constraints with Supply Chain and Server Hardware Engineering.
- Financial Integration: Interface directly with Finance and Product to drive demand capex and opex forecasts off the capacity plan, own the linkage to unit economics, depreciation schedules, and utilization targets, and explain the variances when plan and actuals diverge.