Vice President, FinOps for AI

State Street

. Establish the enterprise FinOps for AI discipline, including scope, taxonomy, methodology, operating model, governance, controls, and performance measures .

Posted 9/29/2026full-timeQuincy • Massachusetts • United StatesLead💰 $110,000 - $188,750 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in establishing FinOps for AI, including governance, cost management, and performance measurement. Proficient in budgeting, forecasting, and optimizing cloud spend across major platforms while ensuring clear communication of financial insights and business outcomes.

Highest-signal resume keywords

FinOps ExperienceCloud Financial ManagementAI Pricing UnderstandingBudgeting And ForecastingPower BI Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Cost ManagementPerformance MeasurementVariance AnalysisOptimization TechniquesFinancial GuardrailsCloud Spend ManagementAI EconomicsData AnalysisModel SelectionCost Estimation

Soft Skills

Analytical JudgmentClear CommunicationResults-Oriented MindsetPartnership BuildingMatrixed Environment Effectiveness

Tools & Technologies

Power BIMicrosoft FabricTableauDatabricksSnowflakeOCIAWSAzureGCPCloud Financial Analytics Tools

Industry Keywords

FinOps FrameworkFOCUS Cost Data StandardsTBM TaxonomyAI GatewaysHyperscaler ServicesAccelerated ComputeCost Per TokenShowbackChargebackCloud Commitment Management

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformTableau

About the role

Key responsibilities & impact

Establish the enterprise FinOps for AI discipline, including scope, taxonomy, methodology, operating model, governance, controls, and performance measures
Create an integrated view of AI cost and consumption across hyperscaler services, accelerated compute, AI gateways, models, tokens, agents, copilots, data platforms, and embedded vendor capabilities
Define unit economics including cost per token, request, session, agent, and use case
Connect AI spending to products, services, business outcomes, and customer value
Lead budgeting, forecasting, scenario modeling, and variance analysis for AI investments
Set allocation, showback, and chargeback standards, including tagging, attribution, shared-cost treatment, and reporting
Identify and deliver optimization opportunities through model selection and routing, prompt and context efficiency, caching, batching, inference right-sizing, accelerated-compute commitments, and retirement of low-value consumption
Track and validate realized savings and cost avoidance
Embed cost estimation, financial guardrails, and onboarding guidance into AI intake and development workflows
Partner with AI and cloud platform teams, engineering, architecture, security, procurement, finance, and business stakeholders
Define reporting and tooling requirements, validate implementation logic, and communicate AI spend, risks, trade-offs, and opportunities through executive showback, leadership reviews, and planning cycles

Requirements

What you’ll need

Practical FinOps or cloud financial management experience
Strong understanding of AI pricing and consumption drivers, including tokens, inference, context windows, model tiers, accelerated compute, licensing, and actual usage behavior
Ability to build a new operating discipline from the ground up
Strong analytical judgment and disciplined distinction among actuals, forecasts, estimates, opportunities, and recommendations
Clear, concise communication of technical cost drivers and business trade-offs
Results-oriented mindset focused on measurable, validated outcomes, documentation, governance, and auditability
10+ years of equivalent relevant experience
Significant experience across FinOps, cloud financial management, technology finance, or cloud and AI engineering
Experience managing or optimizing cloud spend at scale across AWS, Azure, or GCP
Exposure to Databricks, Snowflake, OCI, or similar platforms is beneficial
Direct experience with AI or machine-learning economics strongly preferred
Experience with budgeting, forecasting, allocation, tagging, showback or chargeback, optimization, and cloud commitment management
Familiarity with the FinOps Framework, FOCUS cost data standards, or TBM taxonomy
Proficiency with Power BI, Microsoft Fabric, Tableau, or comparable cloud financial analytics tools
Strong partnership across cloud and AI platform engineering, application teams, architecture, security, procurement, finance, and business leadership
Effectiveness in a matrixed environment
Limited travel may be required

Benefits

Comp & perks

Retirement savings plan (401K) with company match
Basic life insurance
Medical insurance
Dental insurance
Vision insurance
Long-term disability insurance
Optional additional insurance coverages
Paid vacation leave
Paid sick leave
Short-term disability
Family care responsibilities leave
Employee Assistance Program
Annual performance-based incentive compensation
Certain tax advantaged savings plans
Inclusive development opportunities
Flexible work-life support
Paid volunteer days
Employee networks