AI-First Quality Engineering Lead

RBC; Toronto; On-site; CAD 140,000 - 190,000; Full time

Job summary

RBC is seeking an AI-First Quality Engineer Lead to drive a GenAI-powered, AI-driven testing strategy across the software delivery lifecycle. You will lead AI-augmented QA initiatives, architect AI-native automation, and embed intelligence into RBC applications and pipelines.

You will collaborate with product, technology, and platform teams to scale AI-enabled quality as a strategic capability, shaping the future of quality engineering at RBC in Toronto.

Qualifications

• 4 years in QE/test engineering with cloud, distributed systems, APIs, databases, and mainframe environments.
• Experience defining evaluation metrics and AI-driven QA strategies.
• Familiarity with GenAI considerations: hallucination detection, non-determinism, prompt regression.

Responsibilities

• Lead AI-augmented quality engineering across full SDLC.
• Architect AI-native automation frameworks and test ecosystems.
• Pilot AI-powered QE tools to replace manual processes.
• Embed AI into CI/CD pipelines across cloud-native and mainframe environments.
• Prototype AI-driven approaches to test coverage gaps and flaky tests.

Skills

AI-first mindset

QE/test engineering

Cloud & distributed systems

APIs & mainframe

GenAI testing

AI tools in QE

Python/Java/.NET

LLM APIs

Git & DevOps AI

Agentic workflows

Education

CE/CS technical degree

Tools

Git

CI/CD tooling

AI/ML platforms

Job description

Job Description

As AI-First Quality Engineer Lead in QEX & DevOps, you will be a driving force in fundamentally reimagining how RBC builds and delivers software — where AI is not a feature of the QE practice, but the foundation it is built on.

You will partner across technology, product, and platform teams to lead a full shift-left transformation powered by GenAI, intelligent automation, and agentic engineering practices. This is not a role about managing test pipelines — it is about building a quality engineering organization that thinks, operates, and scales with AI at its core.

In this role, you will leverage your full-stack engineering experience and AI fluency to go beyond automating the SDLC. You will embed intelligence directly into RBC’s applications, tools, and delivery ecosystems — using LLMs, AI agents, and predictive analytics to detect risk earlier, accelerate delivery, and raise the bar on software quality at enterprise scale.

We are looking for a bold, future-forward engineer who can sustain and extend RBC’s leadership position in the industry — someone who sees AI not as a productivity add-on, but as a strategic capability to be engineered, governed, and continuously evolved. You will set the vision, build the culture, and model the AI-first mindset that will define the next era of quality engineering at RBC, all while upholding RBC’s Values and guiding principles.

What will you do?

• Lead AI-augmented quality engineering — design and champion testing strategies where AI/ML tools are the default, not an afterthought, across the full software delivery lifecycle
• Build AI-native automation frameworks — architect test ecosystems that leverage LLMs, generative AI, and intelligent agents to autonomously generate, execute, and triage test cases
• evaluate, pilot, and operationalize AI-powered QE tools (e.g., self-healing test suites, AI-based defect prediction, intelligent test selection) to replace manual and legacy processes
• Embed AI into cloud-scale delivery pipelines — integrate AI-assisted quality gates into CI/CD workflows across distributed, cloud-native, and mainframe environments
• Solve hard problems with AI — prototype and validate novel AI-driven approaches to test coverage gaps, flaky test detection, and production observability

What do you need to succeed?

• Hands-on experience using AI/ML tools in a QE context — e.g., GitHub Copilot, LLM-based test generation, AI-driven test analysis platforms
• Proficiency in Python, Java, or .NET with demonstrated use of AI/LLM APIs (Anthropic, OpenAI, etc.) to build intelligent automation
• Strong understanding of agentic workflows and how to apply multi-step AI reasoning to complex testing problems
• Experience building or evaluating AI-powered tools: self-healing selectors, visual AI testing, defect clustering, predictive analytics
• Working knowledge of Git and modern DevOps toolchains with AI integration points (e.g., AI-assisted PR review, intelligent pipeline observability)

Must-have

• AI-first mindset — demonstrated track record of reaching for AI-based solutions first when designing QE strategy, not retrofitting AI onto existing processes
• 4 years in QE/test engineering with expertise across cloud, distributed systems, APIs, databases, and mainframe environments
• Expert in defining EVALs, SKILLS, test and automation strategies with a focus on measurable outcomes — coverage, velocity, defect escape rate — powered by AI-driven insights
• Experience with GenAI application testing considerations: hallucination detection, non-determinism, prompt regression, and responsible AI validation

-Computer Engineering, Computer Science, related (technical) degree/diploma, or related breadth of experience

Nice to Have:

-Prior working experience in financial 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.

Job Skills

Agentic AI, Agentic AI, AI Agents, AI Prompting, Artificial Intelligence (AI), Artificial Intelligence Technologies, Automation Frameworks, Cloud Native, Ecosystems, Generative AI, Generative AI Agents, Information Technology (IT) Infrastructure, Intelligent Agents, Programming Languages, Quality Gates, Software Change Request Management, Software Delivery, Software Development Life Cycle (SDLC), Software Engineering, Software Integration Engineering, Software Product Design, Software Product Technical Knowledge, Software Quality, Software Release Management, Software Systems Engineering {+ 5 more}

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:

2026-08-25

Application Deadline:

2026-10-31

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.