Job DescriptionWhat is the opportunity?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 front-office 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.What will you do?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 testingIdentify, evaluate, and adopt emerging AI tools and techniques that accelerate test coverage and reduce manual effortDeliver quick wins by applying AI-driven testing to high-impact areas of the portfolio, demonstrating measurable improvements in coverage and efficiencyDesign, build, and maintain a scalable QA automation framework that supports full regression testing across 8-10 applications in the TES Data Services portfolioEstablish testing standards, patterns, and reusable components that enable consistent quality practices across all applicationsIntegrate automation frameworks with CI/CD pipelines to enable continuous testing and rapid feedback loopsEnsure framework extensibility to accommodate new applications and evolving data architecturesAnchor QA practices across the entire TES Data Services portfolio, ensuring consistent quality standards for data ingestion, transformation, modeling, and reporting applicationsCollaborate with development teams to shift testing left, embedding quality gates earlier in the delivery lifecycleBuild and manage a lean team of QA automation engineers operating with an AI-first approach to all testing activitiesCoach and mentor team members on AI tool adoption, automation best practices, and capital markets domain knowledgeWhat do you need to succeed?Must-have:Bachelor's degree in Computer Science, Software Engineering, Information Systems,



or related field8-10 years of solid hands-on experience in software testing, QA automation, and quality engineering roles4+ years working in capital markets environments with exposure to trading systems, market data, or financial data platformsDemonstrated experience building QA automation frameworks from scratch and scaling them across multiple applicationsPeople management experience with a track record of building and developing QA teamsExpert proficiency in test automation frameworks and tools (e.G., Selenium, Playwright, pytest, TestNG, or equivalent)Solid programming skills in Python, Java, or both, with the ability to write production-quality test codeHands-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 platformsProficiency with API testing, database validation, and data quality assertion frameworksWorking knowledge of Microsoft Azure services and Databricks environmentsDemonstrated experience using AI tools for test generation, test case creation, or test automation accelerationFamiliarity with AI agents, large language models, and their practical application to software testing workflowsUnderstanding of capital markets trading workflows, trade lifecycle, and market data structuresNice-to-have:Experience building or deploying AI agents for autonomous testing workflowsPrior use of generative AI tools (e.G., Copilot, ChatGPT, or similar) for code generation, test script creation, or specification analysisExperience with performance testing and load testing for data-intensive applicationsFamiliarity with contract testing and schema validation for data pipelinesPrevious experience at a major investment

📌 Senior Qa Automation & Ai Lead (Bedford)
🏢 RBC
📍 Bedford