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Senior AI Financial Operations Analyst

Vizient · Chicago, IL · $102,400–$179,000 a year · Full time

Posted Jun 24, 2026 · We last checked this listing on Oct 5, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Tell me about a time you helped engineers make a cost-conscious decision without slowing them down.

What they are checking: Partnering with technical teams so cost awareness feels helpful rather than like policing.

Tell me about a report or dashboard you built that changed how leaders made spending decisions.

What they are checking: Turning complex consumption data into insight that actually influences decisions.

What would you do

AI spend doubled in a month and nobody knows why. Walk me through how you'd find the cause.

What they are checking: Methodical cost investigation across models, teams and usage patterns, then working with owners to fix it.

A team's AI tool is expensive but leaders love it. How do you approach the conversation about cost?

What they are checking: Framing cost against business value so decisions are made on evidence, not emotion.

About the work

How would you set up cost visibility for generative AI services when spending is driven by tokens, not servers?

What they are checking: Understanding of token-based billing, tagging and allocation so teams can see what their AI use actually costs.

How would you allocate shared AI platform costs fairly across business units?

What they are checking: Designing chargeback or showback models that are fair, understandable and drive better consumption choices.

What levers do you know for reducing AI costs without hurting quality?

What they are checking: Practical knowledge of model selection, caching, prompt size, batching and GPU utilization.

How would you forecast AI spend for next year when usage is growing fast and prices keep changing?

What they are checking: Forecasting under uncertainty with scenarios and clear assumptions instead of a single number.

How do you tie AI spending to business value in a way finance leaders will trust?

What they are checking: Linking consumption to outcomes like time saved or revenue supported, with honest measurement.

What FinOps practices from cloud cost management carry over to AI, and what doesn't?

What they are checking: Whether they see the real differences in AI economics, like variable per-request costs and GPU commitments.

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The full job description

As published by Vizient.

When you’re the best, we’re the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves . We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future. Summary In this role, you will lead the financial governance, operational visibility, and consumption optimization of Vizient’s enterprise AI platforms and generative AI services. You will serve as a key partner in establishing AI FinOps capabilities that enable responsible, scalable, and cost-effective adoption of artificial intelligence technologies across the organization. Reporting to technology leadership, you will drive AI financial management practices across cloud AI services, agentic platforms, token-based consumption models, GPU infrastructure, and AI developer tooling. This role requires a blend of financial acumen, technical understanding, and strategic partnership, with the ability to translate complex AI consumption patterns into actionable insights that optimize cost, improve operational efficiency, and maximize business value. Responsibilities • Lead AI financial operations across enterprise AI platforms, monitoring and managing cloud-based AI spend across services such as Azure OpenAI, Azure AI Foundry, AWS Bedrock, Google Vertex AI, and other emerging AI technologies. • Track, analyze, and optimize AI consumption metrics including token utilization, inference costs, GPU usage, model hosting expenses, vector database consumption, embeddings, and AI agent execution patterns. • Develop forecasting models and financial planning processes to support AI platform growth, capacity management, and long-term investment strategies. • Establish and maintain AI showback and chargeback methodologies that provide transparency into AI consumption and business value realization. • Define and implement governance standards, financial guardrails, and operational controls to ensure responsible and cost-effective AI adoption across the enterprise. • Partner closely with Security, Risk, Legal, Architecture, Cloud Infrastructure, Data & Analytics, and AI Engineering teams to align AI governance practices with organizational policies and strategic objectives. • Provide visibility into enterprise AI tooling adoption, including developer productivity tools, generative AI platforms, and AI orchestration solutions, while identifying and mitigating unsanctioned or shadow AI usage. • Collaborate with engineering teams to optimize AI workloads through improvements in prompt efficiency, token utilization, model selection strategies, inference routing, caching approaches, batching techniques, and GPU resource allocation. • Evaluate hosted and self-managed AI infrastructure options, providing cost optimization recommendations and economic analysis for AI architectures and agent-based frameworks. • Develop executive dashboards, reporting, and analytics that communicate AI consumption trends, financial performance, operational efficiency, and return on investment. • Establish AI unit economics and performance metrics, tracking costs and value realization across use cases, workflows, business capabilities, and enterprise initiatives. • Present financial insights, optimization opportunities, and strategic recommendations to executive leadership and key stakeholders. • Support enterprise AI investment planning, governance programs, and the development of scalable AI operating models and financial management capabilities. • Champion continuous improvement by leveraging data-driven insights to enhance AI financial governance, reporting processes, and operational effectiveness. Qualifications • Bachelor’s degree in Finance, Accounting, Information Technology, Computer Science, Data Analytics, Business, or a related field preferred. • Minimum of 5 or more years of experience in Cloud FinOps, AI Infrastructure, Cloud Operations, Data Platforms, Technology Finance, or a related discipline. • Experience working with public cloud AI services, generative AI platforms, and cloud-based consumption models. • Strong understanding of AI pricing and consumption structures, including token-based, inference-based, and GPU-based cost models. • Experience analyzing cloud financial data, operational telemetry, utilization trends, and technology spending patterns. • Demonstrated ability to build forecasting models, perform financial analysis, and develop executive-level reporting and dashboards. • Strong analytical and problem-solving skills with the ability to identify optimization opportunities and quantify business impact. • Experience collaborating with engineering, architecture, infrastructure, and business stakeholders to drive technology optimization initiatives. • Excellent communication and presentation skills with the ability to translate complex technical and financial concepts for executive audiences. • Experience with Azure OpenAI, OpenAI Enterprise, AWS Bedrock, Google Vertex AI, Azure AI Foundry, or similar AI platforms preferred. • Experience utilizing Cloudability, Azure Cost Management, Datadog, Power BI, or comparable analytics and financial management tools preferred. • Familiarity with AI agent architectures, orchestration frameworks, and emerging AI operational technologies preferred. • FinOps Foundation certification, cloud platform certifications, or related professional credentials preferred. • Experience managing GPU infrastructure or optimizing AI workloads for performance and cost efficiency preferred. • Understanding of AI governance frameworks, responsible AI practices, and enterprise risk management considerations preferred. • Strong knowledge of cloud economics, technology financial management, and AI operational best practices. • Ability to influence cross-functional teams and drive alignment across diverse stakeholder groups while balancing innovation, governance, and financial accountability. #LIJB1 Estimated Hiring Range: At Vizient, we consider skills, experience, and organizational needs in our compensation approach. Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $102,400.00 to $179,000.00. This position is also incentive eligible. Vizient has a comprehensive benefits plan! Please view our benefits here: http://www.vizientinc.com/about-us/careers Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.

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