Strategic Finance Lead — Compute
Leads strategic finance for a GPU compute fleet, modeling capacity, vendor economics, token-serving costs, and investment decisions. Requires at least four years of relevant finance or infrastructure experience and the ability to partner effectively with AI infrastructure engineering teams.
About the job
Responsibilities
- Lead finance for GPU compute spend, including budgeting, monthly forecasting, variance analysis, and financial plan maintenance.
- Build and maintain bottoms-up financial models for the GPU fleet, including capacity forecasts, cost-driver analyses, and investment scenarios.
- Analyze GPU vendor contracts, pricing structures, and cost drivers; identify fleet optimization opportunities.
- Own the compute capacity plan and source of truth for utilization, committed versus consumed spend, and capacity by vendor and cluster.
- Build token-cost curves distinguishing marginal from fully loaded serving costs and translate them into internal and external token pricing.
- Analyze ROI for in-house inference and training, including opportunity costs across chip types, cluster configurations, and workloads.
- Partner with inference and infrastructure engineering to translate serving and training workload dynamics into financial frameworks.
Requirements
- 4+ years of experience in strategic finance, infrastructure investment, private equity, growth equity, consulting, or investment banking.
- Exceptional analytical, problem-solving, and critical-thinking skills.
- Experience building complex financial operating models and synthesizing data into clear insights.
- Experience partnering with technical teams to drive financial optimization and operational outcomes.
- Background in AI, machine learning, or high-performance, large-scale computing infrastructure, including data centers or cloud service providers.
- Proficiency with financial modeling tools.
Nice-to-haves
- Cloud or GPU infrastructure financial management experience with major cloud service providers or neoclouds.
- Experience with committed-use economics, including reserved capacity, savings plans, committed-use discounts, and GPU procurement.
- Expertise in GPU vendor economics, contract structures, and pricing models.
- Experience with chip architecture economics and optimization strategies.
Compensation
- Annual salary: $190,000–$215,000.
Skills
Financial Modeling, Budgeting, Forecasting, Variance Analysis, Gpu Infrastructure, Cloud Computing, Gpu Procurement, Vendor Contracts, Token Pricing, ROI Analysis, Capacity Planning, Machine Learning
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