Finance & Strategy, Compute Infrastructure

AnthropicSan Francisco, CA
23hHybrid

About The Position

We are seeking a Strategic Finance Lead to provide finance leadership for our accelerator investments. In this role, you will be a key partner to our compute teams, providing financial expertise and guidance to optimize our compute investments and drive strategic decision-making In this role, you’ll develop deep expertise in the economics of AI compute, from the unit economics of individual training runs to the long-range financial planning of our accelerator fleet. You’ll build financial models that inform Anthropic’s investment decisions, own planning and forecasting processes for major cost centers, and translate complex technical dynamics into clear financial narratives for leadership. This is a high-impact role for someone who thrives at the intersection of finance and technology, and who is energized by building frameworks from scratch in a fast-moving environment.

Requirements

  • 7+ years of experience in strategic finance, infrastructure investment, private equity, growth equity, consulting, or investment banking, preferably with infrastructure, datacenter, or technology infrastructure experience
  • Exceptional analytical skills with an ability to synthesize data into compelling insights and develop complex financial operating models
  • Extraordinary problem-solving and critical thinking abilities to navigate complex financial challenges
  • Comfort working cross-functionally and are adept at communicating complex financial information to non-finance audiences
  • Proven track record of partnering with technical teams to drive financial optimization initiatives
  • Excitement about working in a fast-paced, dynamic environment and adapt well to change
  • Possess a bias towards action, strong work ethic, and have experience driving operational outcomes under tight timelines
  • Strong relationship building, business judgment, process management, and communication skills
  • Are passionate about Anthropic's mission to build safe, transformative AI systems
  • Background in AI, ML, or high-performance, large-scale computing infrastructure, including data centers, cloud service providers, etc

Nice To Haves

  • 3+ years of experience specifically in cloud infrastructure financial management
  • Experience working directly with major cloud service providers (AWS, GCP, Azure)
  • MBA or other advanced degree in finance, economics, or business
  • Deep expertise in cloud service provider economics, contract structures, and pricing models
  • Experience with chip architecture economics and optimization strategies
  • Proficiency with financial modeling tools and languages (SQL, Python, Excel)

Responsibilities

  • Finance lead for accelerator compute spend, including budgeting, monthly forecasting, variance analysis, and financial plan maintenance
  • Build and maintain detailed bottoms-up financial models for accelerator infrastructure, including long-range forecasts, cost driver analyses, and investment scenario modeling
  • Develop deep expertise in accelerator compute contracts, pricing structures, and cost drivers, and surface optimization opportunities across our infrastructure
  • Support the implementation and management of financial planning tools (e.g., Pigment), ensuring our models and processes scale with the organization
  • Analyze the economics of model training and research compute, including ROI across different dimensions like training run sizes, chip types, data, etc, and track how these economics evolve over time
  • Partner closely with engineering and research teams to understand how training and reinforcement learning processes scale, and translate those technical dynamics into financial frameworks
  • Serve as the finance lead for all data partnerships and human data operations, including budgeting, forecasting, unit economics, and analysis

Benefits

  • competitive compensation and benefits
  • optional equity donation matching
  • generous vacation and parental leave
  • flexible working hours
  • a lovely office space in which to collaborate with colleagues
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