Director, Applied AI Transformation

T. Rowe Price; Baltimore (MD); Hybrid; USD 159,000 - 272,000; Full time

Benefits offered by this job

Hybrid work schedule

Annual bonus eligibility

Health and wellness benefits

Retirement plan

Job summary

T. Rowe Price in Baltimore, MD seeks a Director of Applied AI to lead Global Distribution's two permanent pods, rapidly redesigning targeted workflows with approved AI tools and enterprise capabilities, while building deep partnerships with the business.

You will own end-to-end delivery from design to launch, remove blockers, coach pod members to increase judgment and adaptability, and capture reusable AI patterns to accelerate future transformations, all within a hybrid work model.

Qualifications

• Bachelor's degree or equivalent experience in a relevant field.
• Experience leading multidisciplinary teams through fast-paced transformation.
• Strong understanding of generative AI and emerging AI-enabled ways of working.

Responsibilities

• Lead two permanent Implementation Pods that rapidly redesign workflows using AI tools and enterprise capabilities.
• Establish a repeatable delivery approach with clear accountability and measurable outcomes.
• Drive high-quality execution and remove blockers across cross-functional partners.
• Coach and develop Pod members to build judgment and adaptability for various business challenges.
• Partner with the AI Portfolio, Governance & Value Realization team to assess adoption and impact after launch.

Skills

Leadership

AI strategy

Process transformation

Stakeholder management

Decision making

Education

Bachelor's degree or equivalent experience

Advanced degree preferred

Tools

Agile methodologies

Sprint-based teams

Job description

T. Rowe Price in Baltimore, MD seeks a Director of Applied AI to lead Global Distribution's two permanent pods, rapidly redesigning targeted workflows with approved AI tools and enterprise capabilities, while building deep partnerships with the business.

You will own end-to-end delivery from design to launch, remove blockers, coach pod members to increase judgment and adaptability, and capture reusable AI patterns to accelerate future transformations, all within a hybrid work model.