Senior QA Automation & AI Lead

RBC • Bedford, NS

1d • Onsite

About The Position

The Trading & Execution Services (TES) Data Services team within Capital Markets Technology has elevated data to first-class citizen status, providing strategic solutions for the capture, retention, analysis, and reporting of all transactional data spanning the Capital Markets cross-asset trading lifecycle. Our team is responsible for ingesting and managing cross-asset trading data on our cloud data lake. We consolidate data from internal RBC trading systems and external Independent Software Vendors (ISVs) to deliver high-quality, standardized data products that power front office decision-making across all asset classes. We are building a world-class data organization that leverages artificial intelligence and modern cloud-native architectures to transform how capital markets professionals access and consume data. We are seeking a Senior QA Automation & AI Lead to establish and scale a high-performing, AI-driven quality assurance function across the TES Data Services portfolio. This is a hands-on leadership role for someone who can build a QA team from the ground up, anchoring quality practices across 8-10 applications while leveraging AI agents and automation to maximize coverage with a lean team structure. The successful candidate will demonstrate quick wins through AI-powered testing approaches, then scale those methods into a full automation regression suite spanning the entire portfolio. This role demands a self-driven leader who stays ahead of emerging AI trends, translates them into practical QA capabilities, and coaches their team to operate with an AI-first mindset in everything they do.

Requirements

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or related field
• 8-10 years of solid hands-on experience in software testing, QA automation, and quality engineering roles
• 4+ years working in capital markets environments with exposure to trading systems, market data, or financial data platforms
• Demonstrated experience building QA automation frameworks from scratch and scaling them across multiple applications
• People management experience with a track record of building and developing QA teams
• Expert proficiency in test automation frameworks and tools (e.g., Selenium, Playwright, pytest, TestNG, or equivalent)
• Strong programming skills in Python, Java, or both, with the ability to write production-quality test code
• Hands-on experience with CI/CD integration for automated testing (Jenkins, Azure DevOps, GitHub Actions, or equivalent)
• Experience testing data-intensive applications including ETL pipelines, data lakes, and cloud-native data platforms
• Proficiency with API testing, database validation, and data quality assertion frameworks
• Working knowledge of Microsoft Azure services and Databricks environments
• Demonstrated experience using AI tools for test generation, test case creation, or test automation acceleration
• Familiarity with AI agents, large language models, and their practical application to software testing workflows
• Understanding of capital markets trading workflows, trade lifecycle, and market data structures

Nice To Haves

• Experience building or deploying AI agents for autonomous testing workflows
• Prior use of generative AI tools (e.g., Copilot, ChatGPT, or similar) for code generation, test script creation, or specification analysis
• Experience with performance testing and load testing for data-intensive applications
• Familiarity with contract testing and schema validation for data pipelines
• Previous experience at a major investment bank or capital markets technology firm

Responsibilities

• Define and implement an AI-first QA strategy that leverages AI agents for unit test generation, test case creation from specification documents, and automated regression testing
• Identify, evaluate, and adopt emerging AI tools and techniques that accelerate test coverage and reduce manual effort
• Deliver quick wins by applying AI-driven testing to high-impact areas of the portfolio, demonstrating measurable improvements in coverage and efficiency
• Design, build, and maintain a scalable QA automation framework that supports full regression testing across 8-10 applications in the TES Data Services portfolio
• Establish testing standards, patterns, and reusable components that enable consistent quality practices across all applications
• Integrate automation frameworks with CI/CD pipelines to enable continuous testing and rapid feedback loops
• Ensure framework extensibility to accommodate new applications and evolving data architectures
• Anchor QA practices across the entire TES Data Services portfolio, ensuring consistent quality standards for data ingestion, transformation, modeling, and reporting applications
• Collaborate with development teams to shift testing left, embedding quality gates earlier in the delivery lifecycle
• Build and manage a lean team of QA automation engineers operating with an AI-first approach to all testing activities
• Coach and mentor team members on AI tool adoption, automation best practices, and capital markets domain knowledge

Benefits

• bonuses
• flexible benefits
• competitive compensation
• commissions
• 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 and geographies

What This Job Offers

• Job Type: Full-time
• Career Level: Senior