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Anthropic is seeking a Strategic Finance Lead to provide financial leadership for its compute accelerator investments. This role sits at the intersection of finance and AI infrastructure, requiring deep expertise in the economics of AI compute—from unit economics of individual training runs to long-range financial planning of accelerator fleets.
Key responsibilities include:
- Serve as finance lead for cloud accelerator compute spend, owning 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 compute contracts, pricing structures, and cost drivers; surface optimization opportunities across infrastructure
- Own the source of truth and plan of record for Anthropic's overall compute capacity plan
- Support implementation and management of financial planning tools (e.g., Pigment) to scale processes with organizational growth
- Analyze the economics of model training and research compute, including ROI across training run sizes, chip types, and data; distill insights into actionable frameworks for capacity planning
- Partner closely with engineering and research teams to understand how training and reinforcement learning processes scale, translating technical dynamics into financial frameworks
Ideal candidates bring exceptional analytical skills, extraordinary problem-solving abilities, and a proven track record of partnering with technical teams on financial optimization. The role requires comfort working cross-functionally, translating complex financial information for non-finance audiences, and thriving in fast-paced, dynamic environments.
Preferred qualifications include 7+ years in strategic finance, infrastructure investment, private equity, or consulting (ideally with infrastructure/datacenter/technology experience); 3+ years in cloud infrastructure financial management; direct experience with AWS, GCP, or Azure; MBA or advanced degree in finance/economics; expertise in cloud service provider economics and chip architecture; and proficiency with SQL, Python, and Excel.
