AI Program Manager

Role Overview

• Govern a portfolio of Agentic AI initiatives, ensuring alignment to approved business cases, development stages, and the CAITI operating and delivery model.
• Establish and maintain program cadence, including planning cycles, stage-gate reviews, portfolio reviews, and executive/steering committee updates.
• Manage cross-initiative dependencies, risks, and issues, driving early identification, escalation, and coordinated resolution across squads and workstreams.
• Own program-level reporting across schedule, scope, risks, and financials (CapEx / OpEx), ensuring accuracy, traceability, and audit readiness.
• Coordinate stage-gate progression across Concept, Proof of Concept, MVP, and Production, ensuring readiness criteria are met before advancement.
• Partner with AI Product Managers and Engineering Managers to ensure delivery plans align with portfolio priorities, capacity, and sequencing constraints.
• Support vendor oversight and integration by coordinating timelines, dependencies, and escalation paths in collaboration with Vendor Oversight leads.
• Facilitate portfolio-level forums (program reviews, investment reviews, steering committees), preparing materials and surfacing decisions, risks, and trade-offs.
• Ensure alignment with QA/Validation, regulatory, and information governance expectations by tracking required artifacts, reviews, and approvals at program level.
• Continuously improve program governance practices, templates, and reporting mechanisms to support scaling of the Agentic AI portfolio.

Requirements

• 6+ years in program or portfolio management roles, preferably in technology, AI, or data-driven environments.
• Proven experience managing multiple parallel initiatives with shared dependencies and constrained resources.
• Experience operating within regulated or highly governed enterprise environments.
• Bachelor’s degree in a technical, quantitative, or business discipline, or equivalent practical experience.
• Strong understanding of software development lifecycles, particularly for AI
• or data-intensive systems.
• Ability to engage credibly with Product, Architecture, Engineering, and QA leaders on plans, risks, dependencies, and trade-offs (without owning technical decisions).

Benefits

• Work from home flexibility
• Professional development opportunities