Strategic Finance Lead, R&D and AI Infrastructure

Overview

This role is responsible for guiding strategic R&D investment decisions at the intersection of AI, cloud, compute, and engineering capacity.

You will serve as the dedicated finance partner to the CTO and R&D leadership, turning usage, billing, and headcount data into recommendations that shape major investment decisions before they’re made. Work includes designing the financial architecture for R&D planning and forecasting from the ground up, with AI built into core workflows.

Responsibilities

• Shape how investments are made in AI, cloud, and compute by building an AI-assisted, driver-based economic model connecting usage and billing data across hundreds of SKUs to forecasts and decisions.
• Reduce R&D costs as a percentage of revenue without slowing product velocity by using AI to identify infrastructure spend optimization opportunities and partnering with Engineering to act on them.
• Define AI spend strategy with the Head of AI by tracking spend against ROI by tool and workload and recommending where to commit, consolidate, or cut.
• Provide R&D leaders with an early view of change by owning planning, forecasting, and the headcount capacity model, using automated workflows to flag risks early.
• Lead investment cases from business case through decision to measurement, using AI-assisted scenario analysis to clarify tradeoffs for major infrastructure and R&D commitments.
• Translate R&D performance into a clear executive and board narrative, including what changed, why it changed, and which decisions should follow.
• Rebuild R&D finance around AI, automation, and Pigment to shift time from report assembly toward decision support.

Requirements

• 7+ years across strategic finance, FP&A, business operations, or a related role.
• Demonstrated ability to own consequential work end to end: framing an ambiguous question, structuring analysis, forming a point of view, and driving a recommendation to action.
• Strong data-informed modeling skills, including driver-based forecasts, investment cases, and capacity models built from incomplete or complex data, with AI acceleration.
• Hands-on experience analyzing cloud, compute, AI, or other usage-based technology costs, plus experience partnering with Engineering, Product, Data, AI, or Infrastructure leaders.
• Judgment and communication skills to be a trusted partner to senior technical leaders, challenge assumptions constructively, and explain financial implications in plain language.
• Applied AI fluency, including examples of using AI to improve the speed or quality of modeling, research, or recurring workflows, and how you validate output reliability.
• Curiosity and ability to learn technical systems quickly, translating how AI products and modern infrastructure scale into financial insight.

Preferred Qualifications

• Experience building and maintaining planning, forecasting, and headcount capacity models integrated into recurring business cycles.
• Experience using AI and automation to improve reliability and speed of finance workflows.

Compensation & Benefits

• Not specified in the provided job description.

Location

• Not specified in the provided job description.

Onboarding Milestones

• Within the first 30 days: deliver an initial AI-assisted cloud forecast focused on GCP with AWS coverage as applicable, providing R&D leaders a driver-based view of infrastructure spend direction.
• Within the first 60 days: present a defined AI spend strategy to the CTO, with a clear recommendation on where to commit, consolidate, or cut.
• Within the first 90 days: integrate the R&D capacity model into the planning process so hiring decisions and budget move together.