Lead, AI FinOps & Consumption Governance

ID
2026-8007
Job Locations
US
Category
Technology
Type
Full Time

Overview

Title: Lead, AI FinOps & Consumption Governance

 

Location:  U.S. Remote

 

Pay: $120k - $150k/year DOE

 

Summary: 

New American Funding is scaling AI across software development, borrower- and loan-officer-facing products, and embedded vendor platforms. AI cost grows non-linearly with usage and is driven far more by model selection and usage patterns than by headcount. 

We are hiring a Lead, AI FinOps & Consumption Governance to own the financial discipline behind every dollar of NAF's AI spend — making it transparent, governed, and tied to measurable value. This is a single-threaded ownership role with real decision authority — not an advisory or reporting seat. 

You will set budgets at the platform source, allocate cost to the teams that incur it, and partner with Engineering, Finance, and Analytics to keep spend aligned with ROI. 

Responsibilities

Essential Duties and Responsibilities: 

AI Spend Governance 

  • Own end-to-end visibility and control of all AIspendacross NAF: AI-assisted development tools (Cursor, Claude Code / Anthropic Console), managed-cloud AI (Google Cloud Vertex AI / Gemini Enterprise), Azure Foundry, embedded vendor AI (e.g., Braze, Genesys), and the cloud infrastructure consumed by AI workloads. 
  • Set, monitor, and enforce budgets at the platform source — including pooled and seat-based structures such as Cursor Organizations — 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. For embedded or bundled AI (e.g., Braze, Genesys) that isn't metered at the token or feature level, define a defensible allocation methodology and press vendors for usage telemetry.

Model & Usage Economics 

  • Maintain deep, current fluency in token-pricing mechanics across providers: per-model rates, context-window costs,cachingand batch economics, and committed-use and discount structures. 
  • Partner with Engineering and AI Enablement to define and govern model-selection and routing policy, so high-cost models are used where they earn it and defaults stay economical.
  • Manage commitment strategy — committed-use discounts, enterprise commitments, and reserved-capacity options — against forecast demand.

Allocation, Reporting & ROI 

  • Build cost-allocation pipelines from platform and billing exports into NAF's data-warehouse and BI environment; implement tagging so spend is attributable to team, business unit, model, and workflow.
  • Implement showback and chargeback across pods and business units.
  • Define NAF's AI unit economics (cost per developer, per accepted change, per workflow, per loan or borrower interaction) and work with Finance and Analytics to testspendagainst value. 
  • Deliver monthly executive reporting and on-demand usage and trend reporting; build forecasts tied to product-rollout milestones.

Tooling & Automation 

  • Implement and maintain FinOps tooling for AIspendin alignment with NAF's existing Finance and FinOps function. 
  • Automate cost pipelines using platform and billing exports, SQL and Python transformations, and BI dashboards.
  • Standardize metrics and definitions across all platforms and models so reporting is comparable and trusted.

Authority & Mandate: 

This role carries real decision rights, not just reporting responsibility. The Lead, AI FinOps & Consumption Governance will: 

  • Set and enforce platform- and team-level AI budgets, including reallocation of central reserve capacity.
  • Own idle-seat reclamation policy and execution.
  • Co-own default model policy and cost guardrails with AI Enablement, and gate access to high-cost models.
  • Escalate and, where warranted, apply temporary throttles on anomalous spend.
  • Own the allocation taxonomy and reporting definitions the organization runs on.

Qualifications

Job Competencies / 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-basedspend.
  • Hands-on experience in cloud and SaaS cost and admin consoles (e.g., Google Cloud billing, Anthropic Console, Cursor Organizations, or analogous platforms).
  • Strong working knowledge of LLM pricing mechanics: token billing, context windows,cachingand batching, model price-performance trade-offs, and commitment and discount structures. 
  • 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 (showback/chargeback, tagging, guardrails).
  • 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.

What Success Looks Like (First 12 Months): 

  • Every AI platform has source-level budgets, alerts, and a clear owner; the central reserve operates within a defined utilization band with no overruns.
  • The monthly AI-spend close lands on time with variance explanations — Finance and leadership are neversurprised.
  • Spend is fully attributable to team, business unit, model, and workflow; showback is live and trusted.
  • A model-selection and routing policy is in force and has measurably bent the cost curve versus an uncontrolled baseline.
  • Idle-seat reclamation runs as a standing process, not a quarterly cleanup.
  • Leadership can get accurate AI usage and trend answers on demand, same day.

Scope Boundary: 

This role owns AI-attributable spend and allocation methodology for AI workloads. Non-AI cloud cost management remains under central FinOps, with close partnership for shared infrastructure attribution. 

 

Other Duties: This job may require frequent sitting or standing for long periods of time. This job profile is not intended to be an all-inclusive list of job duties and responsibilities, as one may perform additional related duties as assigned in order to meet the needs of the organization.

Work Authorization: Must be able to verify identity and employment eligibility to work in the U.S.

[EOE/M/F/D/V. Drug-free workplace.]

Physical Demands: The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job.  Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.  Must be able to lift up to ten pounds.  Primary functions require sufficient physical ability and mobility to work in an office setting; to stand or sit for prolonged periods of time; to occasionally stoop, bend, kneel, crouch, reach, and twist; to lift, carry, push, and/or pull light to moderate amounts of weight; to operate office equipment requiring repetitive hand movement and fine coordination including use of a keyboard; and to verbally communicate to exchange information.  VISION:  See in the normal visual range with or without correction.  HEARING:  Hear in the normal audio range with or without correction.

 

 

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