Principal Engineer, AI Governance Platform

Job Description What is the opportunity?

This is a unique opportunity to architect, build, and shape the AI governance platform that enables responsible AI adoption at enterprise scale. As Principal Engineer for AI Governance, you’ll own the end-to-end technical vision for how RBC governs AI — from the governance processes and workflows that ensure compliance, to the integrations that connect governance decisions across multiple enterprise systems, to the reviewer experience that makes complex AI governance decisions understandable and actionable for human reviewers.

You’ll be the technical authority on how governance processes around AI usage are designed and implemented at scale — understanding how AI risk assessments flow through organizational hierarchies, how governance artifacts are produced and consumed by risk systems of record, and how automation can eliminate manual bottlenecks without sacrificing auditability. This requires deep understanding of the interplay between governance policy, technical architecture, and the humans who operate within regulated environments.

You’ll build the platform that ties it all together: a production-grade system that integrates with backend governance services (decision engines, eval platforms, evidence stores), enterprise risk platforms, AI infrastructure (control plane, LLM gateway, agent platforms), and internal tooling — delivering a seamless, unified experience to reviewers, risk specialists, and governance operators. The frontend is a critical piece of this platform, built on modern React/Next.js, but the role demands principal-level thinking across the entire governance stack.

This is a greenfield role with significant ownership. As the governance platform matures and scales across the enterprise, there’s potential to grow this into a team, transitioning from individual contributor to tech lead.

What will you do?

Platform Architecture & Governance Process Design

• Own the technical architecture for the AI governance platform across the full governance lifecycle: intake, assessment, review, escalation, decision, remediation, and audit
• Design how governance processes at enterprise scale are modeled in software — approval chains, delegation of authority, risk classification routing, and policy enforcement
• Architect integrations across multiple enterprise systems (risk book of records, AI infrastructure, eval platforms, evidence stores, telemetry) using APIs, event-driven patterns, and bidirectional data flows
• Collaborate with risk specialists and compliance stakeholders to identify inefficient governance processes and translate them into streamlined, automated technical solutions
• Design and build intelligent agents and automation that generate risk assessment artifacts (risk statements, control mappings, evidence packages, compliance reports) while maintaining auditability
• Implement bidirectional integrations with risk book of records so governance artifacts flow automatically to their systems of record; build browser automation for platforms without API access

Reviewer Experience & Frontend Development

• Own the reviewer experience: design and build UI workflows that enable humans to make defensible governance decisions quickly and with confidence
• Architect and build the governance platform UI as a Next.js/React application with modern patterns (server components, streaming, BFF)
• Build interfaces that present eval evidence, risk classifications, and decision options clearly — escalation screens, remediation tracking, dashboards, and policy configuration UIs
• Design robust API integration, error handling, and fallback strategies for a frontend that depends on multiple upstream services
• Establish component architecture, testing strategies, and observability for the frontend codebase

Technical Vision & Standards

• Establish the technical vision for the governance platform: architecture patterns, engineering practices, and quality benchmarks
• Make and document architectural decisions (ADRs) that enable the platform to scale; influence technical direction across the broader AI governance program
• Set testing strategies (unit, integration, e2e), observability standards, and build the engineering foundation that enables future team growth

What do you need to succeed?

Must-have

• 10+ years of software development experience with demonstrated progression toward principal-level tech…