Product Finance Director, AI Products & GPU Investment Strategy
DatabricksMountain View, CA · Washingtonposted 22h ago
- PayUSD / yr
- $201k – 308k
- Locations
- Mountain View, CAWashington
- Posted
- Oct 15
- 22 hours ago
- Type
- Full-time
- Setup
- On-site
At a glance
Lead product finance strategy for Databricks’ AI business, planning GPU capacity, shaping AI pricing and unit economics, and guiding major investments in compute and frontier model research.
Summarized by AI from the original posting
What you'll do
- Plan GPU supply and demand across clouds
- Drive capacity commitments and procurement strategies
- Lead revenue and margin analytics for AI products
- Model AI product unit economics and partner on pricing
- Define efficiency KPIs such as GPU utilization and cost per token/query
- Run multi-cloud cost allocation and automated financial reporting
- Design ROI and capital allocation frameworks for frontier model research and compute investments
- Build and mentor a product finance team
Requirements
- 0110+ years of experience in Strategic/Product Finance
- 02Experience partnering with senior Engineering and Product executives
- 03Experience building scalable financial systems
- 04Experience building, leading, and developing finance teams
- 05Experience with AI and GPU infrastructure economics preferred
- 06Experience with multi-product P&L preferred
- 07Hands-on proficiency with SQL, Python, or notebook environments preferred
Perks
Skills
Full description
(GAQ427R229)
About the role
AI is the defining platform shift of our generation, and Databricks is right at the center of it. We are looking for a Product Finance leader to scale the fastest growing part of our business with both speed and financial rigor. You will be the primary finance partner to our AI Engineering and Product leaders, with a mandate that spans the full arc of the AI business: planning GPU supply and demand across clouds, shaping how we price AI products, and building the unit economics that will define the margins of this category for years to come.
The impact you will have
- Plan the GPU supply and demand that powers the business
- Establish a trusted, unified GPU demand plan across production inference, internal research, and new product bets so we invest ahead of growth without over-provisioning.
- Drive capacity commitment and procurement strategies across major hyperscalers and emerging neoclouds, optimizing the mix of reserved, spot, and on-demand compute.
- Own AI product economics and partner on pricing
- Lead revenue and margin analytics across the AI product portfolio, turning raw consumption telemetry into a clear read on customer adoption, retention, and product profitability.
- Model the end-to-end unit economics of AI products before they ship, partnering with Product and Pricing to design consumption structures that drive adoption while protecting gross margin targets.
- Establish robust KPIs and operations to drive best-in-class execution
- Partner with Engineering to define north star efficiency KPIs (e.g., GPU utilization, cost per token/query, serverless efficiency) and translate them into committed engineering roadmaps.
- Run tight financial operations, from auditable multi-cloud cost allocation to automated reporting, giving product and engineering leaders real-time visibility into their economic goals.
- Bring finance rigor to the biggest investment decisions
- Design ROI and capital allocation frameworks to evaluate asymmetric bets—including frontier model research, internal compute clusters, and strategic partnerships.
- Build, mentor, and scale a high-performing team of product finance analysts capable of operating at the intersection of deep technical infrastructure and commercial strategy
What we look for
Required
- 10+ years of experience in Strategic/Product Finance, 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.
- A proven track record of partnering directly with senior Engineering and Product executives to influence technical roadmaps and commercial pricing.
- Demonstrated ability to build scalable financial systems from scratch and distill massive, complex telemetry data into models and recommendations leaders act on.
- Experience building, leading, and developing high-output finance teams in fast-moving environments.
Preferred
- Direct experience operating in the AI and GPU economy, including familiarity with training/inference workloads, hyperscaler commitment structures, and neocloud economics.
- Ownership of a multi-product P&L within a high-growth enterprise SaaS, PaaS, or data infrastructure company.
- Hands-on proficiency with SQL, Python, or notebook environments to self-serve insights from raw usage data.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Zone 1 Pay Range$223,800—$307,650 USD
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Zone 2 Pay Range$201,400—$276,850 USD
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.