Strategic Finance Lead, AI Infrastructure & R&D
J
JobgetherAI Infrastructure R&D
Based in the United StatesFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- 7+ years of experience
- Required Skills
- Data Analysis
Requirements
- 7+ years of experience in strategic finance, FP&A, investment banking, investing, consulting, business operations, or a related analytical discipline.
- Demonstrated ownership of complex and consequential work.
- Proven ability to independently take ambiguous problems from initial framing through execution.
- Exceptional financial and analytical capabilities, including driver-based forecasts, investment cases, business models, and scalable decision frameworks.
- Strong understanding of financial planning, forecasting, performance management, investment analysis, and resource allocation.
- Ability to quickly understand technical systems and learn how AI products, cloud infrastructure, and compute environments operate.
- Excellent communication skills, with the ability to translate financial and technical concepts into recommendations for senior leaders.
- Demonstrated judgment and confidence to challenge assumptions and influence senior stakeholders.
- Applied AI fluency, including demonstrated use of AI to improve financial analysis, modeling, or decision-making.
- Strong ownership mentality and comfort working in a fast-moving, high-autonomy environment.
Responsibilities
- Serve as the primary finance partner to the CTO and R&D leadership, influencing investment decisions across AI, cloud and compute infrastructure, engineering capacity, and product development.
- Own the economic framework for AI, cloud, and compute by connecting usage, billing, operational, and financial data to forecasts and investment decisions.
- Lead financial evaluations for major R&D investments, from initial business cases and alternatives analysis through execution, measurement, and post-investment review.
- Own R&D planning, forecasting, and performance management across engineering headcount, AI and cloud infrastructure, compute, software, and external partners.
- Develop driver-based models that identify changes, risks, opportunities, and performance trends early enough for leadership to take action.
- Partner with AI, Engineering, Infrastructure, Procurement, and Accounting teams to improve infrastructure economics, evaluate major commitments, and optimize vendor and technology decisions.
- Analyze strategic questions around infrastructure commitments, workload architecture, technical investments, resource allocation, and build-versus-buy decisions.
- Translate complex R&D and infrastructure performance into concise executive and board-level narratives.
- Establish scalable financial frameworks, operating metrics, and decision mechanisms that can evolve with the organization’s AI and R&D footprint.
- Use AI, automation, and scalable systems to improve the speed, quality, and leverage of financial analysis while reducing manual reporting.
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