Platform Program Manager

Raymond James • Saint Petersburg, FL

1d • Hybrid

About The Position

Raymond James has made a strategic investment in a centralized AI and Machine Learning Platform to accelerate responsible AI adoption across the enterprise. As demand increases across advisory, operations, risk, marketing, and technology teams, successful outcomes now depend less on building capabilities and more on driving organized, intentional adoption. This role exists to drive successful, well-orchestrated adoption of the AI platform at enterprise scale (distinct from software delivery) by creating clarity, structure, and discipline around how AI is requested, adopted, governed, and taken to value.

Requirements

• Exceptionally well-organized; able to manage high volumes of inquiries, use cases, stakeholders, and dependencies with precision.
• Strong understanding of IT financial management, including project funding models, chargeback/showback, and how costs are allocated across initiatives.
• Comfortable coordinating across funded projects, shared platforms, and enterprise services; able to help teams navigate how work is scoped and paid for.
• Solid conceptual understanding of AI, machine learning platforms, data products, and agentic AI, without needing to design or build technical solutions.
• Able to translate between business intent and technical teams, asking the right questions and guiding teams to appropriate solutions.
• Experience operating in complex enterprise environments with multiple governance, risk, and delivery partners.
• High judgment, strong follow-through, and disciplined execution mindset.
• Bachelor’s: Computer and Information Science
• Bachelor’s: Data Science
• Bachelor’s: Information Technology
• High School (HS) (Required)
• General Experience – 10 to 15 years
• Manager Experience - 6 to 10 years

Responsibilities

• AI adoption is organized, visible, and intentional, rather than ad hoc or fragmented.
• Business teams clearly understand what AI capabilities exist, how to access them, and how to use them effectively.
• Use cases are guided from inquiry → selection → execution → completion, with accountability to outcomes.
• Demand for AI is routed efficiently, reducing noise and protecting engineering capacity.
• Agentic AI (MCP-based) adoption is coordinated, governed, and sustainable.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level