Senior Director, AI Architecture

RBC; Toronto; On-site; CAD 180,000 - 280,000; Full time

Benefits offered by this job

Total rewards program

Coaching & development

Flexible benefits

Work‑life balance

Job summary

RBC Technology & Operations is seeking a senior AI architect to define enterprise AI reference architecture and patterns, focusing on RAG, AI agents, and AI-native software delivery. You will shape secure, auditable architectures and ensure scalable, governable AI across on‑prem and cloud environments.

Lead the harness for AI-DLC, enforce quality gates, and align with OSFI guidelines. You will collaborate with Internal Audit, Model Risk, and Cyber teams to balance innovation with risk controls.

Qualifications

• 5+ lines of experience with AI architecture and engineering in enterprise scale.
• Hands-on depth in LLM systems: RAG, agent frameworks, evaluation and inference serving.

Responsibilities

• Define enterprise AI reference architecture and patterns.
• Converge RAG solutions onto a single platform with secure retrieval and cost controls.
• Design agent sandboxing and security architecture with deterministic gates.
• Own AI-DLC harness from spec to release with quality gates.
• Treat skills like code and re-run evals before model upgrades reach teams.
• Route work across frontier and open-weight models with governance and residency rules.
• Define human-oversight tiers in collaboration with audit and risk teams.
• Graduate lab work into the platform and evaluate emerging technologies.

Skills

Big Data Management

Data Modeling

Data Science

Decision Making

Deep Learning

Machine Learning

Predictive Analytics

Programming Languages

Relationship Building

Job description

What is the opportunity?

This leader sets one standard way to build, secure and run AI across RBC Technology & Operations. They own the reference architecture for retrieval-augmented generation (RAG), AI agents, model access and AI-native software delivery (AI-DLC). The role turns the 2030 T&O ambitions, including AI-native delivery and 30% of GenAI volume on open-weight models, into patterns teams actually use.

Job Description

Success means fewer bespoke stacks, faster delivery with maintainable code, and AI that Internal Audit, Model Risk and OSFI can trust.

What will you do

• AI architecture standards as code. Define the enterprise AI reference architecture and approved patterns. Encode them as harness skills, agent constitutions and automated fitness checks, so standards apply at generation time rather than at review.
• Common RAG substrate. Converge the many RAG solutions onto one shared platform: ingestion, chunking, embeddings, hybrid retrieval, reranking and evaluation. Retrieval must respect source entitlements by default. Set a retirement plan for duplicate stacks.
• Agent sandboxing and security architecture. Design the sandbox standard for every agentic workload: ephemer
• AI-DLC harness and quality gates. Own the harness architecture from spec to release. Make quality gates deterministic and mandatory: tests and coverage, static analysis, complexity and duplication limits, dependency and license checks, security scanning and architecture fitness checks. Enforce separation of duties (the agent that writes a change cannot approve it), PR size limits and traceability from spec to deployment.
• Skills and evaluation lifecycle. Treat skills like code: owned, versioned, regression-tested with evals and retired when stale. Re-run evals before any model upgrade reaches teams.
• Model gateway and inference architecture. Route work across frontier and open-weight models by cost, risk and jurisdiction. Build in token metering, caching and data-classification rules so cost and residency are enforced by the platform.
• Risk-tiered control model. Partner with Internal Audit, Model Risk and Cyber to define human-oversight tiers, from human-on-the-loop for low-risk work to human-in-the-loop for payments and core banking. Align with OSFI Guidelines E-23 and B-13.
• Design authority and innovation. Chair AI architecture review, keep decision records and manage exceptions. Graduate proven lab work into the platform and evaluate emerging technology, such as agent protocols and new open-weight models.

What do you need to succeed?

• 15+ years in architecture or engineering, including 5+ years leading architects or engineers at enterprise scale.
• Hands-on depth in LLM systems: RAG, agent frameworks, MCP, evaluation and inference serving on cloud and on-premises GPUs.
• Security architecture for AI, including the OWASP Top 10 for LLM applications, sandboxing and identity for non-human actors.
• Strong DevSecOps and SDLC background; you have shipped quality gates engineers accepted rather than routed around.
• Experience in a regulated industry, ideally financial services under OSFI.
• Credibility with engineers: you still prototype and read code. Able to explain trade-offs plainly to executives and audit.

What’s in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
• Leaders who support your development through coaching and managing opportunities
• Ability to make a difference and lasting impact
• Work in a dynamic, collaborative, progressive, and high-performing team
• A world-class training program in financial services
• Flexible work/life balance options
• Opportunities to do challenging work

Job Skills

Big Data Management, Data Modeling, Data Science, Decision Making, Deep Learning, Machine Learning (ML), Predictive Analytics, Programming Languages, Relationship Building

Additional Job Details

Address: RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO

City: Toronto

Country: Canada

Work hours/week: 37.5

Employment Type: Full time

Platform: TECHNOLOGY AND OPERATIONS

Job Type: Regular

Pay Type: Salaried

Posted Date: 2026-10-27

Application Deadline: 2026-11-20

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

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.