Senior AI Financial Operations Analyst

Vizient•Chicago, IL

3d•$102,400 - $179,000

About The Position

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.

Requirements

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.
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.

Nice To Haves

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.

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.