Staff AI Engineer, AI DLC Platform

RBC

Toronto

On-site

CAD 120,000 - 160,000

Full time

14 days+

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Job summary

RBC is seeking an experienced platform engineer to own the AI production stack, from code promotion through deployment on RBC AI platforms. You will define standards, ensure auditable AI-generated code, and work with risk and governance teams to enforce safe, scalable production practices.

Responsibilities include building the runtime and deployment platform, overseeing containerization, orchestration, secrets management, and observability, while driving reliability and auditable traceability

Qualifications

  • Experience building AI-enabled pipelines with governance and production-readiness considerations.
  • Ability to translate user stories into precise technical specs for AI agents.
  • Familiarity with risk, governance, and audit trails in software delivery.

Responsibilities

  • Build and own the code promotion pipeline from Harness validation output through to Helios deployment.
  • Ensure AI-generated code is auditable and reproducible; explainable and rollbackable.
  • Establish coding standards for AI-assisted development to ensure sound generated code.
  • Collaborate with risk, governance, and engineering teams to codify boundary policies.
  • Build and operate the runtime infrastructure for AI-generated code and sanctioned agents.
  • Own the deployment platform—containerization, orchestration, secrets, scaling, observability.
  • Engineer reliability into the platform with circuit breakers, graceful degradation, zero-downtime deployments.
  • Develop monitoring and alerting to distinguish between bad model, bad code, and bad platform failures.

Skills

Agent Frameworks
Data & Tool Integration
CI/CD & Infrastructure
Automated Testing & QA
Spec-Driven Development
Governance & Security

Tools

LangGraph
CrewAI
AutoGen
FastAPI
gRPC
MCP
Docker
Kubernetes

Job description

What is the opportunity?

The Enterprise Architecture team is undertaking multiple complex enterprise-wide initiatives as part of RBC’s ongoing plan to improve technology management and architectural governance across the organization. In this role you will be responsible for strategically planning and managing successful implementation of the initiatives.

Job Description
What is the opportunity?

The Enterprise Architecture team is undertaking multiple complex enterprise-wide initiatives as part of RBC’s ongoing plan to improve technology management and architectural governance across the organization. In this role you will be responsible for strategically planning and managing successful implementation of the initiatives.

This role will own the platform layer that takes AI-generated code from the Harness and makes it production-grade, safe, and deployable into RBC AI platforms. It will define and enforce the boundary between code that runs in production and agents that run in production — a distinction that has real risk, governance, and architectural consequences for the bank. This role will build pipelines, the runtime, and the standards that make AI delivery trustworthy at scale across RBC.

What will you do?
  • Build and own the code promotion pipeline from Harness validation output through to Helios deployment.
  • Ensure AI-generated code is auditable and reproducible — not a black box that worked once; code that can be reviewed, rolled back, and explained.
  • Establish coding standards for AI-assisted development — the guidelines engineers follow so that what AI generates is structurally sound before it reaches you.
  • Work with risk, governance, and engineering teams to codify this boundary into policy that the Harness and delivery teams can test against.
  • Build and operate the runtime infrastructure that both AI-generated code and sanctioned agents run on within the RBC AI Platforms.
  • Own the deployment platform — containerization, orchestration, secrets management, scaling, and observability.
  • Engineer reliability into the platform — circuit breakers, graceful degradation, rollback mechanisms, and zero-downtime deployments.
  • Build monitoring and alerting that distinguishes between a bad model, bad code, and a bad platform — different failure modes need different responses.
What do you need to succeed?
Must-have
  • Agent Frameworks: Experience with orchestration tools like LangGraph, CrewAI, or AutoGen to build multi-agent workflows.
  • Data & Tool Integration: Ability to design tool contracts, APIs (FastAPI/gRPC), and Model Context Protocol (MCP) connections.
  • CI/CD & Infrastructure: Managing pipelines, container orchestration (Docker/Kubernetes), and infrastructure-as-code.
  • Automated Testing & QA: Using AI to auto-generate test cases, analyze logs, and run validation checks.
  • Spec-Driven Development: Translating user stories and Jira tickets into precise technical specifications that AI agents can execute safely, including spec-kit, open spec.
  • Governance & Security: Setting up human-in-the-loop validation, access controls, and audit trails for automated code
Nice-to-have
  • Demonstrated ability in written and oral communication skills along with strong presentation skills. Ability to determine the information and communication needs of the stakeholders and project.
  • Strong organizational, project management and time management capabilities.
  • A strong understanding of technology and/or financial services industry.
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
  • Flexible work/life balance options
  • Opportunities to do challenging work
  • Opportunities to take on progressively greater accountabilities
  • Access to a variety of job opportunities across business

#TECHPJ

Job Skills

Big Data Analytics, Critical Thinking, Decision Making, Harness Design, Industry Knowledge, LLM Architecture, LLM Evaluation, LLM Guardrails, LLM Orchestration, Machine Learning (ML), Python (Programming Language), Results-Oriented, Software Development Life Cycle (SDLC), Software Engineering, Software Product Design

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: 2026-09-02
  • Application Deadline: 2026-10-02

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.

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