Staff FinOps Analyst

ServiceNow is seeking a Staff FinOps Analyst to support the FinOps Governance team within Global Cloud Services. This senior individual contributor role is focused on improving financial accountability and optimization for the company’s AI investments, with particular attention to cost control, governance, and measurable efficiency gains.

The role sits at the intersection of engineering, cloud finance, and provider relationships across Azure, AWS, GCP, Anthropic, and OpenAI. It is intended for someone who can work independently, build structure around AI spend management, and communicate clearly with senior stakeholders, including VP-level audiences.

The primary objective is to bring the same level of rigor to AI spending that is applied to cloud infrastructure. That includes identifying waste, establishing guardrails, and driving recurring governance processes that help prevent overruns and improve decision-making.

Key Responsibilities

• Define, monitor, and regularly review AI cost and usage KPIs.
• Detect anomalies and outliers in AI usage that may indicate waste, misuse, or optimization opportunities.
• Build and operate anomaly detection processes for unusually high AI usage across models and skill teams.
• Work with engineering teams to investigate issues and implement remediation actions.
• Identify, prioritize, and advance cost optimization opportunities.
• Evaluate trade-offs such as PTU versus pay-as-you-go, model tiering, context reduction, and caching.
• Design governance controls that prevent recurring cost anomalies and overruns.
• Implement AI spend guardrails in coordination with cloud and LLM providers.
• Set budgets, configure alerts, manage commitment structures, and verify contractual rate accuracy.
• Coordinate the AI FinOps governance program across engineering, finance, and provider partners.
• Maintain standards, operating cadence, and documentation for the governance process.
• Prepare executive reporting and presentations on spend trends, optimization progress, and forecasts.
• Own workstreams independently, define scope, manage stakeholders, and deliver outcomes with minimal direction.

Required Skills

• 8 years of related experience with a bachelor’s degree, or 6 years with a master’s degree, or a PhD with 3 years of experience, or equivalent experience.
• Experience applying or evaluating AI in work processes, decision-making, or problem-solving.
• Strong understanding of LLM pricing models.
• Working knowledge of multi-cloud AI services, including AWS Bedrock, Azure OpenAI, and GCP Vertex AI.
• Knowledge of AI cost optimization levers.
• Data analysis skills using SQL and/or Python.
• Ability to build KPI frameworks, identify usage anomalies, and present findings through data visualization.
• Experience with multi-cloud cost governance across AWS, Azure, and GCP.
• Familiarity with budget management, alerting, tagging, and billing APIs.
• Proven cross‑functional collaboration with engineering teams.
• Ability to communicate cost impact and influence technical decisions.
• Strong executive communication and presentation skills.
• Ability to prepare and deliver briefings for VP-level audiences.
• Self‑directed, highly organized, and able to manage multiple concurrent workstreams.
• Bachelor’s degree in a quantitative field such as Computer Science, Engineering, Finance, Mathematics, or a related discipline.

Preferred Skills

• Experience with model routing strategies, prompt engineering, context length management, batch inference, and caching.
• Familiarity with 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 focused on AI cost management standards.

Programming Languages

• SQL
• Python

Tools and Capabilities

• Billing APIs
• Data visualization
• Tagging
• Budget management
• Alerting
• Commitment structures
• GenAI gateway platforms
• LLM proxy platforms

FinOps Responsibilities

• Track and report on AI cost and usage metrics.
• Identify anomalies, waste, misuse, and optimization opportunities in AI spending.
• Establish cost optimization measures and governance controls.
• Set budgets and alerts for AI spend.
• Manage commitment structures and verify contractual rate accuracy.
• Coordinate cross‑functional AI FinOps governance across engineering, finance, and cloud providers.
• Produce executive-level reporting and forecasts on AI spend trends and optimization progress.

• Base salary range of $176,100 to $308,200.
• Equity, where applicable.
• Variable or incentive compensation.
• Health plans.
• Flexible spending accounts.
• 401(k) plan with company match.
• ESPP.
• Matching donations.
• Flexible time away plan.
• Family leave programs.

This role offers the opportunity to shape governance for AI spend at scale within a major enterprise environment. It combines financial discipline, technical fluency, and cross‑functional leadership across engineering, finance, and cloud provider relationships. The position is well suited to someone who wants ownership of an important program and the chance to influence executive‑level decisions with data‑driven insight.

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Tagged as: Compensation Design, Data Analysis, Data Visualization, Python, SQL