# Enterprise AI FinOps Lead

## About the Role

The Enterprise AI FinOps Lead will establish financial transparency, governance, and optimization across Jefferies’ Enterprise AI Program. The role will create a reliable view of spending across models, token consumption, cloud and compute resources, infrastructure, platforms, licenses, partnerships, and usage-based services.

This position will define financial guardrails, investigate cost and usage anomalies, support forecasting and allocation, and provide recommendations that balance cost, performance, risk, and business value.

The role partners with Enterprise AI Program Management, Technology Finance, Engineering, Infrastructure, Procurement, Controllers, and divisional stakeholders. Key outcomes include trusted cost analytics, forecasting, allocation and chargeback support, optimization recommendations, and executive reporting.

## Key Responsibilities

– Establish the Enterprise AI FinOps operating model, including governance, decision rights, controls, service levels, reporting cadence, and ownership.
– Develop a common taxonomy for AI costs across models, tokens, providers, applications, users, teams, divisions, environments, vendors, and cost centers.
– Build authoritative reporting for AI spend, commitments, consumption, forecasts, allocations, and optimization results.
– Design dashboards and executive reporting covering actuals, budgets, forecasts, run rates, anomalies, concentration risks, emerging cost drivers, and required actions.
– Define consumption controls, including budgets, thresholds, alerts, quotas, exception handling, and escalation procedures.
– Partner with Engineering, Infrastructure, Platform, Security, Finance, Procurement, Product, and business teams on cost governance and decision support.
– Evaluate model, hosting, compute, context, service-tier, provider, and platform options against cost, performance, quality, resilience, controls, and business value.
– Identify and track optimization opportunities, including lower-cost routing, reduced token or compute usage, caching, reuse, consolidation, and commercial renegotiation.
– Support annual planning, forecasting, accruals, variance analysis, funding gates, business cases, and value-realization reviews.
– Maintain documentation covering assumptions, data limitations, allocation rules, reporting methods, and forecast changes.
– Support vendor, contract, discount, credit, commitment, renewal, and commercial evaluations.
– Establish data-quality, reconciliation, attribution, allocation, and audit-readiness controls for AI financial reporting.
– Identify and remediate gaps in billing, tagging, ownership, usage telemetry, and organizational data.
– Ensure sensitive financial and consumption information is managed according to applicable policies and access requirements.

## Required Skills

– Significant experience in FinOps, cloud financial management, technology finance, cost management, infrastructure economics, or a related analytical role in a complex organization.
– Experience developing cost transparency, dashboards, forecasts, allocation models, variance analyses, and optimization recommendations for consumption-based technology services.
– Strong knowledge of cloud and technology cost drivers, pricing structures, usage telemetry, budgeting, forecasting, and vendor economics.
– Ability to analyze complex datasets and turn findings into practical decisions, trade-offs, and executive-ready communications.
– Experience working across Engineering, Infrastructure, Finance, Procurement, Product, and business stakeholders.
– Strong attention to detail, control awareness, commercial judgment, and written and verbal communication skills.

## Preferred Skills

– Experience analyzing or managing costs related to AI, machine learning, GPUs, model APIs, or token-based consumption.
– Familiarity with FinOps Foundation principles, cloud cost-management practices, and showback or chargeback models.
– Experience in investment banking, capital markets, regulated financial services, or major cloud, AI, observability, or business-intelligence tooling environments.

## Cloud Platforms & Technologies

### AI and Consumption

– Enterprise AI
– Machine learning
– AI models and model APIs
– Token-based consumption

### Cloud and Infrastructure

– Cloud services
– Compute and GPU resources
– Infrastructure
– Hosting
– Platforms and service tiers

### Data and Reporting

– Usage telemetry
– Dashboards
– Observability tooling
– Business-intelligence tooling

## FinOps Responsibilities

– Establish financial transparency across AI models, providers, applications, users, teams, divisions, environments, and cost categories.
– Manage budgets, forecasts, allocations, showback, chargeback, commitments, and executive financial reporting.
– Monitor consumption patterns for uncontrolled growth, idle or duplicated services, inefficient configurations, policy breaches, and avoidable spending.
– Investigate anomalies and track corrective actions through completion.
– Develop bottom-up forecasts using adoption, workload, user, model, token, compute, and pricing assumptions.
– Perform scenario analysis for growth, new use cases, model and pricing changes, vendor commitments, and infrastructure decisions.
– Assess whether spending is producing intended value and identify viable alternatives.
– Evaluate provider economics, commercial structures, build-versus-buy decisions, hosting options, discounts, credits, and commitment utilization.
– Recommend actions to reduce waste, improve purchasing leverage, and limit unfavorable lock-in.
– Incorporate consumption costs and unit economics into business cases and return-on-investment tracking.
– Maintain controls for data quality, reconciliation, cost attribution, allocation, optimization measurement, and audit readiness.
– Balance financial controls with legitimate experimentation and high-value business outcomes.

## Compensation

– Full-time salary range: **$175,000–$200,000**

## Benefits

Eligible employees may receive:

– Medical, dental, and vision coverage
– 401(k)
– Life, accident, and disability insurance
– Wellness programs
– Paid time off and paid holidays
– Paid parental leave

## Why You Might Be Interested

This role offers the opportunity to build the FinOps operating model for an enterprise AI program and influence decisions across Finance, Engineering, Infrastructure, Procurement, and business teams. The position combines cost analytics, forecasting, governance, commercial analysis, and AI consumption economics. It also provides scope to shape how AI investments are evaluated, controlled, and connected to measurable business value.