Databricks
Product Finance Director, AI Products & GPU Investment Strategy
$201K–$308K
Mountain View, California +3 · Director · Full-time · Posted Oct 15, 2026
- Location
- Mountain View, California
San Francisco, California
Seattle, Washington
Mountain View, California - Experience
- 10+ years of Strategic/Product Finance experience; complemented by foundational training in Investment Banking, Private Equity, or Management Consulting.
About the job
Leads product finance for Databricks’ AI business, covering GPU capacity planning, AI product pricing and economics, operational KPIs, and investment decisions.
What you'll do
- Plan GPU supply, demand, procurement, and capacity commitments across cloud providers and neoclouds.
- Analyze AI product revenue, margins, and unit economics; partner with Product and Pricing on consumption structures.
- Set financial and efficiency KPIs, improve cost reporting, evaluate investments, and build and lead a product finance team.
What they ask for
- 10+ years of Strategic/Product Finance experience, complemented by foundational training in Investment Banking, Private Equity, or Management Consulting.
- Deep fluency in consumption-based business models, public cloud infrastructure costs, unit cost analysis, and gross margin optimization.
- Track record of partnering with senior Engineering and Product executives to influence technical roadmaps and pricing; experience building scalable financial systems and turning complex telemetry into actionable models.
- Experience building, leading, and developing high-output finance teams in fast-moving environments.
Nice to have
- Direct experience in the AI and GPU economy, including training/inference workloads, hyperscaler commitments, and neocloud economics; ownership of a multi-product P&L in high-growth enterprise SaaS, PaaS, or data infrastructure.
- Hands-on proficiency with SQL, Python, or notebook environments.
Pay
$223,800 — $307,650 USD (base salary); $201,400 — $276,850 USD (base salary)
Tools
SQL, Python
AI focus
Finance strategy for AI products and GPU investments, including AI product economics and pricing, GPU supply and demand planning, and evaluation of frontier model research and compute investments.
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