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About the Role

AI Architecture Governance & Insights establishes enterprise-wide AI architecture standards, patterns, and governance frameworks for RBC. As a Lead Data Scientist, you will build the standards, patterns, and tools that enable RBC's AI transformation at scale, acting as the architect behind our architecture practice.

Responsibilities

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)
Track Agent adherence to standards/patterns and report on compliance/non-compliance
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
Coordinate cross-pillar architecture decisions and continuously improve certification processes
Build tools, Agents, and MCPs to automate architecture governance (e.g., CALM Visualizer, SafeAI tooling)
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
Partner with EA, LOB governance groups, and GCS on security architecture alignment
Drive POCs for new AI capabilities and governance approaches
Work directly with lines of business to understand needs and architect practical solutions

Requirements

Strong grasp of AI technologies (LLMs, agents, RAG, agentic systems, AI infrastructure)
Hands-on coding ability. Must be comfortable building tools, automations, and prototypes
Experience with infrastructure-as-code, API design, and modern development practices
Proven ability to design scalable, secure, maintainable systems
Understanding of platform patterns, reusability, and governance at scale
Can translate abstract requirements into concrete, implementable designs
Experience creating technical standards, patterns, or reference architectures
Understanding of compliance frameworks and how to operationalize governance
Comfortable working with Architecture Review Boards or similar governance bodies
Adaptability: Thrive in fast-paced environments where priorities shift
Parallel execution: Comfortable context-switching between strategic work and tactical delivery
Strong collaboration skills, working across EA, Security, Engineering, and business teams
Bias for action: Build, test, iterate
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

Skills

Active Learning
Application Integrations
Detail-Oriented
Group Problem Solving
Programming Languages
Software Development Life Cycle (SDLC)
AI technologies (LLMs, agents, RAG, agentic systems, AI infrastructure)
Infrastructure-as-code
API design
Modern development practices
Scalable system design
Secure system design
Maintainable system design
Platform patterns
Reusability
Governance at scale
Technical standards creation
Pattern creation
Reference architecture creation
Compliance frameworks
Operationalizing governance
Architecture Review Boards

Location

RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO
Toronto
Canada

Work Type

Full time

Benefits

Bonuses
Flexible benefits
Competitive compensation
Commissions
Stock options where applicable

About the Company

RBC's AI Group is the AI accelerator for RBC, with a focus on driving the shift from early-stage AI projects to scaled, client outcomes that amplify the impact of RBC's people.
The AI Group is responsible for advancing research into emerging use cases across generative and agentic AI, while maintaining expertise in security, responsible AI and regulatory expectations.
The Business Enablement function within the AI Group partners with LOBs and Functions to set AI ambition, originate transformation opportunities, and frame programs for delivery — ensuring RBC remains at the frontier of AI-enabled value creation.
At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC.
We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world.
Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities.
RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

Equal Opportunity

RBC is an equal opportunity employer committed to diversity and inclusion.
We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors.
Disability-related accommodations during the application process are available upon request.