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Lead, AI FinOps & Consumption Governance

New American Funding · United States · 1 mo ago
RemoteRemoteOTHR$120k–$150k/yrFull-time

Overview

New American Funding is scaling AI across various products and platforms. The Lead, AI FinOps & Consumption Governance role involves owning the financial discipline behind AI spend, ensuring transparency, governance, and alignment with ROI.

Responsibilities

  • Own end-to-end visibility and control of all AI spend across NAF: AI-assisted development tools, managed-cloud AI, Azure Foundry, embedded vendor AI, and cloud infrastructure consumed by AI workloads.

  • Set, monitor, and enforce budgets at the platform source, including pooled and seat-based structures, and establish guardrails, usage alerts, and anomaly detection per platform.

  • Own seat lifecycle economics: allocation, utilization tracking, and reclamation of idle or low-value seats.

  • Create attribution where vendors don't expose it. Define defensible allocation methodologies for embedded or bundled AI and press vendors for usage telemetry.

  • Model and usage economics: Maintain deep fluency in token-pricing mechanics, partner with Engineering and AI Enablement to define and govern model-selection and routing policy, manage commitment strategy, and implement cost-allocation pipelines.

  • Allocation, Reporting & ROI: Build cost-allocation pipelines, implement showback and chargeback, define NAF's AI unit economics, deliver monthly executive reporting, and build forecasts tied to product-rollout milestones.

  • Tooling & Automation: Implement and maintain FinOps tooling, automate cost pipelines, standardize metrics and definitions, and own allocation taxonomy and reporting definitions.

Qualifications

  • Bachelor's degree in a quantitative or technical field, or equivalent experience.

  • 5+ years in FinOps, cloud or SaaS cost management, or technical finance — including direct ownership of variable, usage-based spend.

  • Hands-on experience in cloud and SaaS cost and admin consoles.

  • Strong working knowledge of LLM pricing mechanics.

  • Proven forecasting and financial modeling for variable-usage systems.

  • Strong analytical toolkit: SQL, Python, BI tools, and advanced spreadsheet skills.

  • Track record embedding cost discipline within engineering and product teams.

  • Excellent communication — able to translate complex cost structures for both technical and executive audiences.

Preferred Qualifications

  • Experience in regulated financial services or mortgage.

  • Familiarity with the economics of AI-assisted developer tooling.

  • Experience working with cloud billing platforms (Azure, GCP, AWS).

  • FinOps Foundation certification.

  • Experience building cost governance frameworks for emerging technologies like AI.

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