Job Description & Details
This is a specialized financial operations role bridging the gap between heavy enterprise AI investments and strict budget controls. If you understand token-based pricing, cloud consumption models, and how to build chargeback mechanisms for AI workloads, this gig gives you a lot of autonomy to tame complex infrastructure spend. You will be instrumental in making sure the company's AI initiatives actually make financial sense.
What You'll Actually Be Doing
Expect to spend your days knee-deep in complex usage data, figuring out how much token consumption, compute utilization, and foundational model licensing are actually costing the business. You'll partner directly with engineering, procurement, and finance teams to design showback and chargeback models that accurately allocate AI spend back to individual business units. It's a lot of translating raw cloud metrics into actionable unit economics and convincing leadership where optimization is desperately needed.
The Core Tech Stack
Your toolkit here revolves around advanced financial modeling, deep data manipulation, and modern reporting platforms. You need to be lethal in Advanced Excel and capable of building executive-ready dashboards in Power BI or Microsoft Fabric. More importantly, your technical stack includes a deep mental model of AI economics—understanding inference costs, API pricing structures, and how cloud infrastructure scales under heavy machine learning workloads.
Interview Expectations
Expect the hiring team to test your real-world grasp of AI economics by asking how you would build a chargeback model for a shared LLM deployment with wildly fluctuating token consumption. They want to see past standard cloud FinOps and hear how you account for unpredictable foundation model costs and API pricing tiers. Another favorite line of questioning will revolve around contract negotiations; they'll likely present a scenario where a major AI vendor is pushing an unfavorable licensing renewal, and they want to hear your strategy for balancing technical necessity with hard financial leverage.
Application Advice
Make sure your resume doesn't just read like a generic FP&A profile. Highlight specific metrics around cloud cost optimization, TCO analyses, and showback or chargeback models you've personally built and administered. Keywords like "AI FinOps", "Token-based Pricing", "Unit Economics", "Microsoft Fabric", and "Cost Allocation" need to jump off the page if you want to clear the ATS and convince the hiring manager you've done this exact job before.