Solid working proficiency in artificial intelligence, with a track record of applying AI tools to test design, test data generation, debugging, and automation maintenance, and of guiding peers on effective use. Working knowledge of AI risk management and a commitment to responsible and ethical AI use, including validating AI-generated artifacts before adoption.
Education
Bachelor’s, Master’s, or PhD degree in Computer Science, Information Technology, or a related field, or equivalent practical experience
Responsibilities
Senior QA role taking a leading technical position in test strategy and automation for an Asset Management application, product area, or set of features. Acts as a technical reference for quality in that scope and contributes to the broader QA strategy and automation roadmap
Drive the end-to-end test strategy within scope, covering functional, integration, API, database, performance, and cross-environment testing, and support release readiness decisions with clear quality evidence
Design, build, and evolve the automation framework and shared testing libraries used by QA engineers in scope, contributing to coding standards, review practices, and flake and maintenance policies
Design parallel and multi-threaded test execution in containerized environments to reduce feedback time and scale coverage as the product grows
Integrate automated suites into continuous integration and continuous delivery pipelines, including quality gates, test selection, and reporting, and support release practices such as canary releases and production verification
Define and report quality metrics within scope and translate them into recommendations on risk, priorities, and testability improvements for engineering and product leadership
Lead root-cause analysis of complex, cross-component, or data-integrity defects and drive the resulting fixes and preventive measures with the relevant teams
Represent quality in architecture and design reviews, influencing testability, observability, and non-functional requirements early in the lifecycle
Contribute hands-on expertise and proposals to the broader QA strategy and automation roadmap in partnership with QA and engineering leadership
Champion the effective use of AI-assisted tooling in test development, maintenance, and debugging, including good practice for validating AI-generated tests and data before adoption
About the Team
You’ll be joining a global, cross-functional team within Moody’s Analytics Asset Management business that develops software, advanced analytics, and data-driven solutions supporting investment decision-making across global financial markets. The team brings together engineers, analytics and data specialists, and financial technology experts across multiple regions, and continuously explores emerging technologies, including artificial intelligence, to improve products and delivery. In this role you will work alongside senior QA and engineering leaders and have direct influence on how quality is engineered into platforms used by leading organizations worldwide.
