AI Quality Engineer

Job Description WHAT IS THE OPPORTUNITY? Are you a talented, creative and results-driven professional who thrives on delivering high-performing applications? Come join us!

Global Functions Technology (GFT) is part of RBC’s Technology and Operations division. GFT’s impact is far-reaching as we collaborate with partners from across the company to deliver innovative and transformative IT solutions. Our clients represent Risk, Finance, HR, CAO, Audit, Legal, Compliance, Financial Crime, Capital Markets, Personal and Commercial Banking and Wealth Management. We also lead the development of digital tools and platforms to enhance collaboration.

We are seeking an exceptional AI Quality Engineer to architect and lead our transition from traditional QA to an AI-Led Software Development Lifecycle (AISDLC) testing framework. This role is foundational to modernizing how we validate AI-driven features, optimize test coverage, and ensure data quality at scale across complex organizational domains.

This is a strategic hire that combines hands-on engineering excellence with organizational leadership capacity, establishing RBC as a leader in intelligent, continuous validation.

WHAT WILL YOU DO?

• Design AI/ML-powered test optimization frameworks – Architect intelligent test coverage systems using advanced methodologies to intelligently prioritize and select test cases, reducing manual testing overhead while maintaining quality standards
• Establish AISDLC governance and quality standards – Define comprehensive testing standards, governance models, and quality metrics that apply across the organization for AI-enabled systems and features
• Integrate AI-driven validation into CI/CD pipelines – Embed real-time, continuous quality assurance throughout development workflows to enable rapid, safe deployments at scale
• Implement predictive validation and monitoring systems – Deploy continuous validation with proactive observability tools that detect data drift, validate model performance, and identify quality issues in parallel with development
• Build scalable, adaptive test automation infrastructure – Create intelligent automation platforms that dynamically evolve with AI systems, including complex validation for data quality, feature behavior, and system performance
• Define enterprise data quality protocols – Establish robust validation processes for large-scale datasets across key functions (brand marketing, compensation, database systems) to ensure reliable AI-enabled features
• Translate business requirements into technical automation – Bridge organizational needs with scalable, intelligent validation logic that demonstrates ROI through deployment velocity, test cycle reduction, and improved time-to-market
• Build center of excellence and develop specialized teams – Establish RBC’s QE function as a leading center for AI testing practices while upskilling existing staff in modern automation and AISDLC methodologies
• Create strategic modernization roadmaps – Develop comprehensive plans for transforming QE capabilities across complex, interconnected domains with clear governance balancing speed and quality

WHAT DO YOU NEED TO SUCCEED? Must have:

• 7+ years test automation architecture with 3+ years in AI/ML systems testing; expert proficiency in AI/ML testing frameworks, MLOps, CI/CD integration, and programming (Python, Java);
• Experience with test data management and AISDLC methodologies.
• Strategic & Architectural Capability: Proven ability to design scalable QA frameworks across interconnected domains; track record modernizing legacy QA processes; experience translating business requirements into technical automation strategies; strong understanding of financial services compliance testing.
• Leadership & Team Building: Proven ability to build, mentor, and lead high-performing teams; experience establishing centers of excellence; demonstrated organizational influence and stakeholder management.
• Communication & Adaptability: Exceptional communication skills translating complex technical concepts for diverse audiences; comfort operating in ambiguous environments with emerging technologies; ability to establish new practices and frameworks from the ground up.

Nice-to-have :

• Background in financial services or regulated industry QA
• Experience with model monitoring, MLOps, or ML pipeline validation
• Familiarity with Robotic Process Automation (RPA) testing, performan…