Portfolio and Strategy Lead – Agentic AI

Job Description What’s the opportunity?

RBC’s Agentic AI Enablement team is a specialized engineering force that embeds directly into strategic use cases, delivers production‑grade agentic systems, and builds institutional muscle for agentic AI  need a Portfolio & Strategy Lead to own the “what” and “when” of the team’s engagement portfolio, deciding what enters the pipeline, in what order, and ensuring the team’s finite capacity is deployed against the highest‑value opportunities.

Reporting to the Senior Director, Agentic AI Enablement, the Portfolio & Strategy Lead owns intake prioritization, capacity planning, portfolio reporting, and engagement sizing. You’ll lead a team of Engagement Product Managers and a Portfolio Analyst, building the product management and strategy function that bridges demand (Business Enablement) and supply (Engineering Pods + Delivery). You ensure the team works on the right things at the right time with the right resourcing, while your EPMs ensure each engagement is scoped correctly and delivers against business requirements.

This role requires someone who can think strategically about portfolio composition, communicate trade‑offs clearly to senior leaders, and operate with rigor in a fast‑moving environment where engagement demand consistently outpaces capacity.

• Own the intake process for new engagement requests, jointly prioritizing with Business Enablement based on strategic fit, value potential, executive sponsorship, and data readiness
• Maintain a transparent, prioritized pipeline that balances near‑term delivery commitments with strategic bets
• Ensure every engagement entering the pipeline has clear qualification criteria met before squad formation is triggered
• Say no (or not yet) with conviction when capacity or qualification thresholds aren’t met

• Ensure EPMs maintain scope integrity, requirements quality, and stakeholder alignment across their assigned engagements
• Allocate EPM coverage across engagements based on intensity (dedicated for complex engagements; shared for lighter ones)
• Set standards for requirements documentation, engagement charters, acceptance criteria, and adoption strategies
• Build a cohesive product management practice with shared standards while allowing engagement‑level adaptation

• Own capacity planning across the engineering pod structure, maintaining real‑time visibility into available FDE capacity
• Trigger squad formation decisions based on engagement priority, sizing requirements, and available capacity
• Partner with the Delivery Lead on resourcing trade‑offs when demand exceeds supply
• Manage ADT lending allocation decisions, balancing external support commitments against core enablement delivery
• Recommend squad sizing (light / standard / heavy) in partnership with Principal Engineers and EPMs based on engagement complexity

• Maintain portfolio‑level reporting for leadership: engagement status, pipeline health, capacity utilization, and value realization
• Track and report on engagement outcomes and success metrics post‑delivery, informing future prioritization decisions
• Provide executive‑ready portfolio updates for steering committees and leadership forums
• Identify patterns across engagements that inform strategic direction (e.g., recurring demand signals, capability gaps, reuse opportunities)

• Translate enterprise AI strategy into portfolio‑level planning for the Enablement team
• Align engagement portfolio with broader organizational priorities and funding cycles
• Identify capability gaps and inform hiring/investment decisions based on demand patterns
• Partner with Business Enablement on demand forecasting and pipeline development
• Inform team growth decisions (e.g., when sustained lending triggers the case for additional pods)

• Ensure structured handoffs at each lifecycle stage (Intake → Scope & Size → Build & Deliver → Transfer & Close → Measure & Learn)
• Own the “Measure & Learn” phase: capturing engagement outcomes, lessons learned, and…