Head of Finance

present of AI; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Wafer in San Francisco is seeking a hands-on Senior Finance lead to own the monthly close and audit, manage usage-based billing and revenue recognition, and build financial models for planning. The role focuses on metered AI inference costs and revenue, with exposure to GPU/compute contracts and cash planning.

The ideal candidate has led a close and model at a startup, can query raw usage data, and translate it into actionable numbers for the founders, while supporting fundraising and investor

Qualifications

• Must have owned a close and a model at a startup
• Experience with metered or infrastructure revenue
• Comfortable with a large variable cost base

Responsibilities

• Own the monthly close and audit process
• Manage usage-based billing and revenue recognition
• Build financial model and planning
• Manage GPU and compute contracts and cash
• Support fundraising and investor reporting

Skills

Monthly close

Revenue recognition

Usage-based billing

Financial modeling

Cash management

Fundraising

Investor reporting

Job description

Finance & Legal San Francisco FullTime Senior level

This is a hands on finance lead role at a small, fast growing company. The person must run the monthly close and audit, handle usage based billing and revenue recognition, build the financial model and planning, manage GPU and compute contracts and cash, and support fundraising and investor reporting. A strong candidate has owned a close and a model at a startup, has worked with metered or infrastructure revenue, is comfortable with a large variable cost base, and can work directly from raw data.

How it fits the AI era

The company sells AI inference, so the finance work centers on metered usage and compute costs that shift with demand. AI tools can speed up reconciliation and reporting, but the judgment on revenue recognition, contract terms and cash planning stays with the person. The role rewards someone who can query usage data directly and turn it into numbers the founders can act on.

How it builds AI experience

Working here means learning how AI inference is priced and billed, how GPU capacity commitments affect margins, and how usage data reconciles to reported revenue. That gives direct exposure to the economics of AI infrastructure. To prepare, a candidate could practice building reconciliations from raw usage data and modeling variable compute costs.

Worth showing

• Owned monthly close
• Usage based billing
• Revenue recognition
• Fundraise and diligence

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Wafer

An AI inference provider that uses AI agents to tune GPU code, which it says lets open models run faster on AMD and Nvidia chips.