AI Architecture Governance & Insights establishes enterprise-wide AI architecture standards, patterns, and governance frameworks for RBC. We create the standards and certification criteria that ensure AI solutions are built safely, securely, and in alignment with the enterprise strategy. We deliver insights into our AI capabilities and compliance, and we partner with security, enterprise architecture, and business teams to ensure AI is built responsibly and strategically As a Lead Data Scientist in the Governance & Insights team, you will build the standards, patterns, and tools that enable RBC's AI transformation at scale.

You'll be the architect behind our architecture practice, creating governance artifacts, maintaining CALM/Agent Card standards, supporting the AI Architecture Review Board, and building automation to surface insights across our AI estate. You’ll work in a fast-paced environment where priorities shift rapidly based on leadership needs, platform evolution, and emerging governance challenges. You might pivot from defining reference architectures to building a MCP server to developing compliance dashboards within the same week.

Create and maintain AI governance artifacts: patterns, standards, reference architectures, and technical whitepapers Manage CALM standard evolution and its alignment to AI platforms (Athena, Nova, Atlas) Define and evolve the AI Technical Reference Model, capability catalog, and license-to-build criteria Play a key role in the AI Architecture Review Board, including preparing materials, reviewing submissions, and contributing architectural opinions Represent AI Architecture perspectives at broader governance forums (Technology Infrastructure and Security review boards)



Partner with engineering teams to review solution designs and provide architectural guidance Deliver AI asset insights: catalog state, capability coverage, compliance metrics, and adoption trends Modernize the SafeAI process and integrate with AI platform governance Publish Architecture Decision Records (ADRs) for cross‑cutting decisions Surface governance data through AI Architecture Agents Translate business and technical problems into implementable designs, then contribute hands‑on development Research emerging AI technologies and evaluate vendor solutions Drive POCs for new AI capabilities and governance approaches Technical Depth Strong grasp of AI technologies (LLMs, agents, RAG, agentic systems, AI infrastructure) Hands‑on coding ability. You must be comfortable building tools, automations, and prototypes yourself Can translate abstract requirements into concrete, implementable designs Experience creating technical standards, patterns, or reference architectures Thrive in fast‑paced environments where priorities shift based on leadership asks and platform evolution Comfortable context-switching between strategic work (standards development) and tactical delivery (tool building, ARB support) build, test, iterate Passion for AI Governance Stay current with internal/external AI trends and innovation Genuine interest in making AI technology accessible, well‑governed, and production-ready Desire to build the infrastructure that enables responsible AI adoption at enterprise scale Be part of a dynamic & flexible working environment A comprehensive Total Rewards Program including bonuses and versatile benefits, competitive compensation, commissions, and stock options wh #

📌 Lead Data Scientist, Data Science (Toronto)
🏢 Royal Bank of Canada
📍 Toronto