Senior Manager: FinOps and AI Consumption

Overview

Mayer Brown is an international law firm positioned to represent the world’s major corporations, funds, and financial institutions in their most important and complex transactions and disputes. We are recognized by our clients as strategic partners with deep commercial instincts and a commitment to creatively anticipating their needs and delivering excellence in everything we do.

We are a collegial, collaborative firm where highly motivated individuals with an unwavering commitment to excellence receive the opportunity, support, and development they need to grow, thrive, and realize their greatest potential all while supporting the Firm’s client service principles of excellence, strategic partnership, commercial instinct, integrated strengths, innovation, and collaboration across our international firm.

If you thrive in a collaborative environment that values exceptional client service, initiative, professionalism, responsiveness, and adaptability, we invite you to consider joining our Information Technology department as aSenior Manager:
Fin Ops and AI Consumption. This role is available in any of Mayer Brown's US offices.

The Senior Manager:
Fin Ops and AI Consumption owns cost governance across the firm's full cloud and AI estate. This role tracks and forecasts cloud infrastructure spend broadly, while going deep on the firm's most technically demanding and fastest-growing cost driver: token and model consumption across AI platforms and providers.

This is a quantitative and technical role with a clear business purpose that will give Pricing, Finance, and practice leadership a reliable answer to what an AI-enabled workflow actually costs us to deliver. As we build pricing, contract, and consumption models around AI-enabled services, those decisions need to be grounded in credible, traceable cost data, rather than vendor list pricing, broad assumptions, or guesswork.

Essential Functions:

Cloud Fin Ops

• Own cost governance, forecasting, and chargeback (if implemented) across the firm's full cloud estate
• Manage rightsizing, reserved/committed-use capacity, and vendor rate optimization as cloud usage grows with the firm's data and AI footprint
• Establish tagging and attribution standards so cost can be tied to business unit, practice group, and eventually matter

AI & Token Economics

• Build and maintain a working model of token and inference cost across the firm's AI providers and platforms (Harvey, Copilot, Microsoft Legal Agent, Azure AI, OpenAI, Anthropic, and future platforms)
• Track cost-per-workflow and cost-per-matter for AI-enabled work, broken out by model used, task type, and volume of consumption
• Maintain broad, current knowledge of the AI model landscape - cost structures, context-window pricing, agent/tool-call cost multipliers, and the cost/performance tradeoffs between models Advise on the cost implications of model selection and workflow design
• Monitor how vendor pricing models are evolving (token-based, seat-based, hybrid) and assess what each means for the firm's cost exposure as usage scales

Pricing Enablement

• Partner directly with Pricing to translate workflow and matter-level AI cost data into inputs they can use to price services, structure AFAs, and evaluate consumption-based contract terms
• Support review of contract and consumption models as the firm evaluates migration to token-based and other usage-based pricing structures
• Provide Pricing and Finance with scenario modeling e.g., cost impact of a given model mix or workflow design at a given volume to inform pricing decisions

Governance & Reporting

• Establish budget guardrails and consumption thresholds for AI usage as adoption scales across practice groups
• Represent cost and consumption considerations in…