VP, AI FinOps & Cost Governance

STATE STREET CORPORATION

Quincy (MA)

On-site

USD 110,000 - 189,000

Full time

3 days ago

Be an early applicant

Application generator

Stand out for this role — generate a tailored resume and cover letter in about a minute.

Get past ATS filters

Benefits offered by this job

401K with company match

Health insurance

Paid time off

Employee assistance program

Performance-based awards eligibility

Job summary

State Street Corporation invites a strategic FinOps executive to lead the AI cost governance program. You will align technology, engineering, finance, and procurement to drive cost transparency, budgeting, and optimization across AI platforms, gateways, and accelerated compute.

You will build unit economics, provide forecasts, and guide executive decision-making with clear showbacks and actionable insights.

Qualifications

Bachelor’s degree in Finance, Accounting, Economics, CS, Engineering, IS, or related field preferred.
10+ years of equivalent relevant experience.
Significant experience across FinOps, cloud financial management, technology finance, or cloud and AI engineering.
Direct experience with AI/machine-learning economics, such as model/inference costs or AI licensing.

Responsibilities

Establish the enterprise FinOps for AI discipline including scope, taxonomy, methodology, operating model, governance and performance measures.
Create integrated view of AI cost across hyperscaler services, accelerated compute, models, tokens and data platforms.
Define unit economics—cost per token, request, session, agent—and connect AI spend to products and outcomes.
Lead budgeting, forecasting, scenario modeling and variance analysis for AI investments.
Set allocation, showback and chargeback standards with tagging and reporting by unit and use case.
Identify optimization opportunities through model selection, context efficiency, and accelerated compute commitments.
Track realized savings and cost avoidance with clear distinction from estimates and forecasts.
Embed cost estimation and guardrails into AI intake/workflows before development begins.
Partner with AI and cloud platform teams to secure data and guide consumption decisions.
Define reporting and tooling requirements and communicate spend and risks to leadership.