Role Summary

We areseeking anAI FinOps Engineerto help drive the cost-effective, scalable, and well-governed adoption of artificial intelligence across the firm. This role will sit at the intersection ofAI platform engineering, cloud financial operations, data infrastructure, and enterprise governance, helping ensure that AI capabilities are delivered with strong financial discipline, operational transparency, and risk awareness.

The AI FinOps Engineer will work closely with teams acrossTRP Labs,EnterpriseArchitecture,Engineering,Finance, Procurement, DataScience, Security, Risk, and business stakeholdersto provide visibility into AI-related spend, improve resource efficiency, support forecasting and budgeting, and help establish standards for sustainable AI usage.

This role will support a broad range of AI workloads, including machine learning, advanced analytics, and generative AI use cases, across cloud and enterprise technology environments.This is a technical, hands-on role. You will work at the API level to instrument workloads,identifyinefficiencies, and engineer solutions that reduce organizational cost without degrading capability. A key output of this work is translating AI usage findings into best practices.

Why This Role Matters

As T. Rowe Price continues to expand its use of AI and advanced analytics, it is critical that these capabilities are delivered with strong operational rigor, cost transparency, and governance. The AI FinOps Engineer will help the firm scale AI in a way that is efficient, responsible, and aligned with enterprise priorities.

Responsibilities

• Develop andmaintaincost transparencyfor AI and machine learning workloads, includingcompute, storage, networking, model training, inference, and third-party AI platform usage.
• Create and managereporting, dashboards, and KPIsto track AI-related spend,utilization, efficiency, and business value across teams and use cases.
• Partner witharchitecture,engineering, platform, and data science teams toidentifyopportunities to improvecost, performance, andutilizationof AI infrastructure and services.
• Analyze AI workload consumption patterns and recommend optimization strategies related to:(1) model selection and deployment approach(2) compute and GPU sizing(3) workload scheduling(4)storage lifecycle management(5) inference efficiency(6) vendor and API usage
• Support the design and implementation ofshowbackand chargeback modelsfor AI-related services to improve accountability and decision-making.
• Build forecasting and budgeting models for AI platform usage, cloud consumption, and external vendorspend.
• Help define and enforcelightweightgovernance standardsfor AI infrastructure, including tagging, budgeting, provisioning controls, usage monitoring, and lifecycle management.
• Collaborate with Finance and Procurement to supportvendor evaluation, pricing analysis, contract planning, and consumption optimizationfor AI platforms and services.
• Partner with Risk, Security, and Compliance stakeholders to ensure AI cost optimization practices align with enterprise controls and regulatory expectations.
• Automate cost management and governance processes using scripting, infrastructure-as-code, and cloud-native tooling.
• Evaluate tradeoffs among hosted AI services, internally managed platforms, and open-source model deployments with a focus on cost, scalability, security, and operational supportability.
• Contribute to firmwide best practices forresponsible, efficient, and scalable AI adoption.

Qualifications

Required:

• Bachelors degree or equivalent work experience inComputer Science, Engineering, Information Systems, Finance, Data Analytics, ora relatedfield.
• Experience in one or more of the following areas:FinOps, cloud engineering, platform engineering, DevOps,MLOps, data engineering, or infrastructure cost management.
• Deep familiarity with LLM pricing mechanics: context windows, caching, batching, input/output token splits, and tier structures.
• Strong understanding of cloud cost drivers, includingcompute, storage, networking, and managed platform services.
• Familiarity with AI/ML workload patterns such as model training, fine-tuning, batch inference, real-time inference, and data pipeline processing.
• Experience with at least one major cloud platform, such asAWSorAzure.
• Experience using cloud cost management, observability, or reporting tools.
• ProficiencyinPython, SQL, or similar scripting/query languages.
• Experience building dashboards, reports, or analytics to support cost transparency and operational decision-making.
• Strong analytical and problem-solving skills with the ability to translate technical usage into financial and business insights.
• Strong communicationand collaboration skills, with the ability to work effectively across technical, operational, and business teams.

Preferred:

• Experience supportinggenerative AI or large language model workloads, including token-based pricing models and inference cost optimization.
• Familiarity with enterprise AI and data platforms such asDatabricks, Snowflake, SageMaker, Azure ML, or similar technologies.
• Understanding ofGPUutilization, accelerator economics, and performance-cost tradeoff analysis.
• Knowledge of enterprise tagging, cost allocation, and budget governance practices.
• Experience inafinancialservices or other highly regulatedenvironment.
• Familiarity with enterprise risk, security, and control expectations related to technology and data platforms.
• Relevant certifications in cloud platforms, FinOps,Technology Business Managementor infrastructure engineering.

FINRA Requirements

FINRA licenses are not required and will not be supported for this role.

Work Flexibility

This role is eligible for hybrid work, with up to three days per week from home.

Base Salary Ranges

Please review the job posting for the location of this specific opportunity.

Placement within the range provided above is based on the individuals relevant experience and skills for the role. Base salary is only one component of our total compensation package. Employees may be eligible for a discretionary bonus, which is determined upon company and individual performance.

Benefits