As Director of AI-First Quality Engineering & 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. As Director of AI-First Quality Engineering & 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 leader 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. 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 Drive AI-first tooling adoption — 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 Ensure QEX platforms are fully operationalized — own monitoring, reliability, and continuous improvement of AI-augmented QE ecosystems Grow an AI-fluent team — mentor engineers in prompt engineering, responsible AI use, and integrating AI tools into daily QE workflows 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.) 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) Ability to communicate AI strategy and tradeoffs clearly to both technical teams and business stakeholders AI-first mindset — demonstrated track record of reaching for AI-based solutions first when designing QE strategy, not retrofitting AI onto existing processes ~10+ years in QE/test engineering with expertise across cloud, distributed systems, APIs,



databases, and mainframe environments ~4+ years of people management in Agile/DevOps environments, including building teams that have adopted AI tooling ~ Expert in defining 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 Prior working experience in financial industry 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 versatile benefits, competitive compensation, commissions Ability to make a difference and lasting impact from a local-to-global scale Automation Frameworks, Business Process Improvements, CI/CD, Creative Visioning, Generative AI, Information Technology (IT) Infrastructure, Information Technology Trends, Intelligent Agents, Intelligent Automation (IA), IT Architecture, IT Service Management (ITSM), Long Term Planning, Prompt Engineering, Quality Engineering, Responsible AI, Software Release Management, Strategic Thinking, Systems Software, Test Case Design, Testing Strategies Employment Type: Full time 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. #

📌 Director, QEX & AI-First Quality (Toronto)
🏢 RBC
📍 Toronto