## About the Role

The Lead, Enterprise AI FinOps will establish and run the financial governance framework for company-wide AI usage. This role is responsible for visibility into AI spend, show-back, optimization, budgeting, forecasting, and stakeholder engagement across a multi-cloud, SaaS, and on-premise AI environment.

This is a hands-on leadership role focused on AI-specific cost drivers such as models, tokens, prompts, agents, embeddings, context windows, and RAG systems. The position requires the ability to turn usage telemetry into practical insights, optimization initiatives, and executive-level reporting that supports responsible AI adoption.

The role also owns full budget management for the Enterprise AI department and works closely with Finance, Procurement, Cloud FinOps, Legal, platform owners, and senior business leaders. This is a full-time onsite position in San Diego, CA, with onsite work required five days per week.

## Key Responsibilities

– Establish the operating model for AI FinOps, including visibility, cost accountability, show-back, optimization cadence, and leadership reporting.
– Define the processes, metrics, and governance needed to control cost while supporting AI adoption.
– Own usage visibility across cloud, on-premise, internal, and SaaS AI platforms.
– Identify major cost drivers and highlight where spend growth is exceeding value delivery.
– Design and implement show-back methodology with allocation rules for shared platforms, model gateways, agent platforms, RAG systems, and SaaS AI.
– Deliver monthly and quarterly show-back reporting for business unit and functional leaders.
– Own AI cost forecasting and budget planning using usage trends, adoption growth, model pricing, and optimization efforts.
– Manage departmental budget activities, including planning, tracking, accruals, purchase planning, and vendor cost visibility.
– Partner with Finance, Procurement, Cloud FinOps, Legal, and platform owners to maintain financial discipline.
– Identify and drive cost reduction opportunities without reducing business value or adoption.
– Lead recurring reviews with high-usage teams to reduce waste and improve efficiency.
– Produce executive-ready reporting for CIO, Finance, IT, and business unit leaders.
– Develop narratives that explain cost growth, business value, adoption health, and efficiency gains.
– Define KPIs that distinguish healthy adoption from uncontrolled consumption.

## Required Skills

– 8+ years of experience in FinOps, cloud cost management, technology finance, IT financial management, or enterprise analytics.
– Experience managing budgets, forecasts, financial reporting, and cost optimization programs.
– Strong understanding of cloud cost models in Azure, AWS, or GCP.
– Ability to analyze large-scale usage data and convert it into actionable business insights.
– Strong stakeholder management experience across senior leaders, finance partners, and technical teams.
– Experience building dashboards, KPIs, and recurring operating reviews.
– Excellent executive communication skills, both written and verbal.
– Ability to work independently and build operating models and business processes from scratch.
– 7+ years of IT-related work experience with a bachelor’s degree, or 9+ years without a bachelor’s degree.
– 4+ years of leadership experience in projects or programs.

## Preferred Skills

– Experience with AI, GenAI, or LLM platforms.
– Familiarity with token-based pricing or AI platform operations.
– Knowledge of tokens, embeddings, RAG, agents, context windows, model routing, prompt optimization, and inference workloads.
– Multi-cloud cost management experience.
– On-premise infrastructure cost allocation experience.
– Cross-functional partnership experience with Finance, Procurement, Legal, Contracts, and Engineering.
– Proficiency with Power BI, Tableau, Looker, Databricks, Snowflake, BigQuery, SQL, Python, or similar tools.

## Cloud Platforms & Technologies

### Cloud Providers
– Azure
– AWS
– GCP

### AI / Platform Concepts
– AI platforms
– GenAI
– LLMs
– Tokens
– Embeddings
– RAG
– Agents
– Context windows
– Model routing
– Prompt optimization
– Inference workloads

### Data & Analytics
– Databricks
– Snowflake
– BigQuery
– SQL
– Python

### Reporting & BI
– Power BI
– Tableau
– Looker

## FinOps Responsibilities

– Establish financial governance for enterprise AI usage.
– Build cost visibility and accountability for AI spend.
– Create and run show-back processes, including allocation for shared AI platforms.
– Own AI budget planning, forecasting, accruals, and vendor cost tracking.
– Identify cost reduction opportunities and recurring waste.
– Support executive reporting on spend, value, adoption, and efficiency.
– Define KPIs for AI consumption health and cost control.

## Benefits

– Competitive annual discretionary bonus program.
– Opportunity for annual RSU grants.
– Competitive benefits package.
– Pay range: $161,700.00 – $242,500.00.

## Useful Links

– LinkedIn: https://www.linkedin.com/jobs/view/4432642625
– Application: https://www.linkedin.com/jobs/view/4432642625

## Why You Might Be Interested

This role offers the opportunity to shape how enterprise AI spend is governed across cloud, SaaS, and on-premise environments. It combines financial leadership, data analysis, and executive communication in a setting where AI adoption and cost discipline must advance together. The position is well suited to someone who can build operating models from the ground up and translate complex usage patterns into clear business decisions. It also provides direct ownership of the Enterprise AI department budget and regular exposure to senior leadership.