Lead, AI FinOps & Consumption Governance

AI Spend Governance:

• Own end-to-end visibility and control of all AI spend across NAF: AI-assisted development tools, managed-cloud AI, Azure Foundry, and embedded vendor AI.
• Set, monitor, and enforce budgets at the platform source, establish guardrails, usage alerts, and anomaly detection.
• Own seat lifecycle economics: allocation, utilization tracking, and reclamation of idle or low-value seats.

Model & Usage Economics:

• Maintain deep, current fluency in token-pricing mechanics across providers: per-model rates, context-window costs, caching and batch economics.
• Partner with Engineering and AI Enablement to define and govern model-selection and routing policy.
• 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 data-warehouse and BI environment.
• Implement showback and chargeback across pods and business units.
• Deliver monthly executive reporting and on-demand usage and trend reporting; build forecasts tied to product-rollout milestones.