# Staff Al Engineer, AI Governance Platform at RBC

RBC is hiring a Staff Al Engineer, AI Governance Platform in Toronto, Canada. Level rates it Works on AI ●●●○; you can [apply on Level](https://jobsbylevel.com/go/a73d2b40-875c-47ca-bba1-4585f371cb9c?utm_medium=ai-agent).

AI Level 3, AI centrality 68 out of 100. TORONTO, Ontario, Canada.

## Details

- Company: [RBC](https://jobsbylevel.com/companies/rbc)
- AI level: AI Level 3 (score 68 out of 100)
- Location: TORONTO, Ontario, Canada
- Posted: October 15, 2026
- Apply: https://jobsbylevel.com/go/a73d2b40-875c-47ca-bba1-4585f371cb9c?utm_medium=ai-agent

## Prepare for this job

The job page lists 3 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/staff-al-engineer-ai-governance-platform-at-rbc-2f2ba5

## Description

Job Description What is the opportunity? This is an opportunity to contribute to building the reviewer experience for AI governance at enterprise scale. As Staff Engineer for AI Governance UI & Reviewer Experience, you'll help build the governance platform's frontend—a Next.js/React 19 microservice that sits in front of backend governance services and makes complex AI governance decisions understandable and actionable for human reviewers. You'll contribute to building the UI that enables reviewers to make defensible governance decisions: presenting evidence clearly, surfacing risk classifications, routing escalations, and tracking remediation. You'll also help build automation that streamlines governance workflows, working alongside senior engineers to create seamless integrations with enterprise risk systems. This is a hands-on Staff Engineer role where you'll implement production-grade React applications that serve as the human interface to RBC's AI governance plane. You'll work under the guidance of Principal Engineers to implement the technical vision for the governance UI and follow established standards and patterns. You'll work on genuinely hard UX problems: how do you present assessment questions and LLM generated responses (and corresponding evals) so reviewers trust them? How do you implement escalation workflows that get the right decisions to the right authority? How do you make audit evidence legible to humans while maintaining traceability ? What will you do? You will contribute to building the governance UI microservice: Frontend Development (Hands-On) Implement features for the governance platform UI using Next.js 14+ / React 19 Build components using the App Router architecture with server components and streaming Develop reviewer workflows using TypeScript, TanStack Query, and modern React patterns Implement BFF (Backend-for-Frontend) patterns to integrate with governance APIs Build components following established architecture, state management, and data fetching patterns Write and maintain Playwright + Jest test suites for UI reliability Implement frontend features with proper error boundaries, loading states, and accessibility Risk Workflow Development & Automation Collaborate with risk specialists and senior engineers to understand governance processes and implement technical solutions Build automation features and intelligent agents to generate risk assessment artifacts (risk statements, control mappings, evidence packages, compliance reports) Implement integrations with risk book of records (Archer/Maverick) to push governance artifacts Implement browser automation using tools like Playwright for platforms without API connections Contribute to building the audit artifact repository within the governance platform Implement integrations between the governance platform and risk book of records following established patterns Contribute to integrating individual risk domain workflows into the overall governance layer Reviewer Experience & Workflow Implementation Build reviewer workflows that enable humans to make good governance decisions quickly Implement interfaces that present eval evidence, risk classifications, and decision options clearly Build escalation screens that route high-consequence decisions to the right authority Implement remediation tracking interfaces that make governance outcomes visible and actionable Build evidence presentation layers that reduce cognitive load while maintaining completeness Contribute to building dashboards for monitoring governance operations, decision patterns, and system health Implement configuration UIs for governance policy, thresholds, and control registry management API Integration & Backend Connectivity Integrate with backend governance services: decision engine, eval platform, evidence store, telemetry systems Consume APIs from agent platforms, control plane/gateway, and risk registries (Archer/Maverick) Implement event-driven updates and real-time data

The description is cut here. Read the full offer: https://jobsbylevel.com/jobs/staff-al-engineer-ai-governance-platform-at-rbc-2f2ba5

Source: https://jobsbylevel.com/jobs/staff-al-engineer-ai-governance-platform-at-rbc-2f2ba5

## Cite this page

Level. https://jobsbylevel.com/jobs/staff-al-engineer-ai-governance-platform-at-rbc-2f2ba5.

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