Staff FinOps AI Governance Lead

ServiceNow · San Francisco

Manufacturing & OperationsEngineering, Infrastructure and OperationsFull-timeposted 2mo ago

Company Description

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

Job Description

Team

Join FinOps Governance team that is part of the Global Cloud Services organization.

You’ll apply your expertise in AI cost management and data-driven optimization to lead programs that bring accountability and control to ServiceNow’s AI investments. Working closely with engineering teams building AI-powered skills and experiences, cloud finance leadership, and provider relationships with Azure, AWS, GCP, Anthropic and OpenAI, you’ll be the connective tissue between technical usage and financial discipline.

About the role

We are looking for a Staff FinOps AI Governance Lead to drive financial accountability and optimization across ServiceNow’s AI spend. This senior individual contributor role combines deep AI infrastructure literacy, data-driven governance, and cross-functional program leadership to ensure our AI investments are managed with the same rigor as our cloud infrastructure. The ideal candidate understands the economics of LLMs as well as they understand engineering and will thrive operating independently while engaging VP-level stakeholders with confidence and clarity.

What you get to do in this role:

Define, track, and systematically review AI cost and usage KPIs; identify anomalies and outliers that signal potential waste, misuse, or optimization opportunities.
Design and operate an anomaly detection framework to surface suspiciously high AI usage across models and skill teams, and engage engineering collaboratively to investigate and remediate.
Quantify, prioritize, and propose cost optimization opportunities—evaluating levers such as PTU vs. pay-as-you-go trade-offs, model tiering, context reduction, and caching—and drive them to measurable outcomes.
Design preventive governance controls so that cost anomalies and overruns, once identified, are systematically prevented from recurring.
Define and implement AI spend guardrails in coordination with cloud and LLM providers: set up budgets, configure alerts, manage commitment structures, and ensure contractual rate accuracy.
Coordinate the AI FinOps governance program across engineering, finance, and cloud provider relationships—maintaining a clear operating model with documented standards and a regular review cadence.
Prepare and deliver VP-level reporting and presentations on AI cost trends, optimization progress, and forward-looking forecasts, translating technical data into clear financial narratives.
Operate as a self-starter and self-sufficient program owner: define scope, manage stakeholders, and drive workstreams to completion with minimal direction.

Qualifications

To be successful in this role you have:

Strong working knowledge of LLM pricing models, multi-cloud AI services (AWS Bedrock, Azure OpenAI, GCP Vertex AI), and AI cost optimization levers.
Proficiency in data analysis using SQL and/or Python to build KPI frameworks, identify usage anomalies, and communicate findings through data visualization.
Hands-on experience with multi-cloud cost governance across AWS, Azure, and GCP, including budget management, alerting, tagging, and billing API familiarity.
Proven cross-functional collaboration skills with engineering teams—ability to communicate cost impact, influence technical decisions, and drive efficiency improvements.
Outstanding communication and executive presentation skills; comfortable preparing and delivering briefings to VP-level audiences on complex technical and financial topics.
Self-directed and highly organized, with the ability to manage multiple concurrent workstreams independently in a fast-paced environment.
Bachelor’s degree in a quantitative field (Computer Science, Engineering, Finance, Mathematics, or related).

Nice to have:

Experience with AI optimization techniques: model routing strategies, prompt engineering, context length management, batch inference, and caching.
Familiarity with provider-level budget and commitment tools: Azure Cost Management, AWS Budgets, GCP Billing controls, and provider credit management.
Understanding of agentic AI cost patterns including per-agent token attribution, multi-agent cost multiplication, and RAG workflow cost implications.
Experience with GenAI gateway or LLM proxy platforms for token metering, rate limiting, and cost attribution.
Prior involvement with FinOps Foundation working groups or industry communities on AI cost management standards.

JV20

For positions in this location, we offer a base pay of $176,100 - $308,200, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

Additional Information

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. 

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance.

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.