Strategic Finance Lead, AI Infrastructure & R&D

As a Strategic Finance Lead for AI Infrastructure & R&D at TRM Labs, you serve as the finance owner for the company's AI, cloud, and compute infrastructure investments and product development. Reporting to the VP of Finance and partnering directly with the CTO, Head of AI, and R&D leadership, you shape how TRM allocates investment across these critical domains. You sit at the center of consequential R&D decisions, designing the financial frameworks and operating mechanisms that translate complex technical and financial information into recommendations that influence senior leadership.

What you'll do

• Serve as the primary finance partner to the CTO and R&D leadership, shaping how TRM invests across AI, cloud and compute infrastructure, engineering capacity, and product development.
• Own the economic framework for AI, cloud, and compute, connecting usage, billing, and operating data to forecasts and investment decisions.
• Lead the financial evaluation of major R&D investments from initial business case through decision, execution, and measurement.
• Own R&D planning, forecasting, and performance management across engineering headcount, AI and cloud infrastructure, compute, software, and external partners, surfacing changes early enough for leaders to act.
• Partner with the Head of AI, Engineering, Infrastructure, Procurement, and Accounting to improve infrastructure economics, evaluate major commitments, and translate analysis into action.
• Turn complex R&D performance into a clear executive and board narrative: what changed, why it changed, and which decisions should follow.
• Redesign R&D finance around AI, automation, and scalable systems so that more time goes toward shaping decisions and less toward assembling reporting.

What you bring

• 7+ years of experience across strategic finance, FP&A, investment banking, investing, consulting, business operations, or a related analytical role.
• A track record of independently owning consequential work end to end: framing ambiguous questions, structuring analysis, developing a point of view, and driving recommendations toward action.
• Exceptional financial and analytical skills, including the ability to create driver-based forecasts, investment cases, and scalable decision frameworks from incomplete or complex data.
• Strong communication skills and judgment to become a trusted partner to senior technical leaders, challenge assumptions constructively, and explain financial implications in plain language.
• The ability and curiosity to learn technical systems quickly, understand how AI products and modern infrastructure are built and scaled, and translate those operating realities into financial insight.
• Applied AI fluency: you can demonstrate how you have used AI to improve the speed or quality of analysis, modeling, research, or recurring workflows, and how you evaluate the reliability of its output.
• Relevant domain experience in one or more of the following areas: supporting Engineering, Product, Data Science, AI, or Infrastructure organizations; analyzing cloud, compute, AI infrastructure, or other usage-based technology costs; or evaluating vendor commitments, technical investments, product economics, and build-versus-buy decisions.

What we offer

• Substantial ownership from the beginning with direct exposure to senior leadership and the latitude to shape decision frameworks and operating mechanisms.
• The opportunity to scale this role using AI, automation, and scalable systems to expand what you can own as a senior individual contributor.
• Potential to shape and build the team supporting the function as the mandate grows, with people leadership available as a credible growth path but not required.

About TRM Labs

TRM Labs provides AI-powered intelligence solutions that help public and private sector agencies investigate and disrupt crime. TRM is a Series C company with $220M in total funding, backed by Goldman Sachs, Bessemer, Y Combinator, Thoma Bravo, and others. Headquartered in San Francisco, TRM operates as a distributed-first company with hubs in Los Angeles, San Francisco, New York, Washington D.C., London, and Singapore.