Software Dev Engineer Test II

Overview
MetLife is seeking experienced Software Development Engineers in Test (SDETs) to drive quality engineering across its digital and AI transformation programmes. This role demands a blend of strong programming fundamentals, test automation expertise, and hands-on experience with AI-powered tools to accelerate quality across the software delivery lifecycle in an Agile, cloud-native environment.
Key Responsibilities
Agile Testing & Collaboration
Adopt Agile/Scrum methodologies across the software delivery lifecycle; participate in sprint planning, estimation, and documentation of test strategies and acceptance criteria aligned with business and technical requirements.
Collaborate closely with development and product teams to identify, diagnose, and resolve code defects, test failures, and regressions; manage defect tracking and produce clear, actionable bug reports.
Test Automation & Execution
Design, develop, and maintain scalable test automation frameworks (Web, API, Mobile/Native) using Java or TypeScript, adhering to coding standards, best practices, and reusable design patterns.
Execute automated and manual test cases for new builds and regression cycles; analyse test reports, troubleshoot failures, and repair broken test scripts to ensure continuous quality coverage.
Contribute to CI/CD pipelines (Azure DevOps, Jenkins) and participate in performance, integration, and cloud-native testing on Azure; leverage Docker and Selenium Grid for scalable, distributed test execution.
Programming, Data Structures & Design
Apply strong programming fundamentals—data structures, algorithms, and design patterns (e.g., Page Object Model, Factory, Singleton)—to build maintainable, efficient, and reusable automation components that scale with the product.
AI-Augmented Testing & Innovation
Leverage AI-powered developer tools (e.g., GitHub Copilot, Cursor, Claude CLI) to accelerate test script creation, code review, and process optimisation across areas of the SDLC, measurably improving team productivity and delivery speed.
Integrate LLMs and modern AI/ML frameworks into testing and automation pipelines to enable intelligent test generation, anomaly detection, defect prediction, and automated root-cause analysis.
Candidate Qualifications
Education
Bachelor’s degree in Computer Science, Engineering, or an equivalent technical discipline.
Experience
3–8 years of hands-on software testing and automation experience, preferably within financial services, insurance, or technology domains; demonstrated track record of delivering quality at speed in Agile environments.
Skills & Competencies
Programming & Design: Proficiency in Java or TypeScript (JavaScript a plus); solid understanding of OOP, data structures, algorithms, and design patterns to write high-quality, scalable automation code.
Test Automation: Proven experience with Selenium, TestNG, Cucumber, RestAssured, or equivalent frameworks; hands-on expertise across Web, API, and integration test automation.
Cloud & DevOps: Working knowledge of Azure DevOps, Docker, Jenkins, and Selenium Grid; experience with TDD/BDD practices and Agile/Scrum delivery methodologies.
AI Tools & Frameworks: Demonstrated use of AI coding assistants (GitHub Copilot, Cursor, Claude CLI); practical experience integrating LLMs and AI/ML frameworks into testing or automation workflows to drive productivity and innovation.
Performance Testing: Hands-on experience with JMeter, BlazeMeter, or equivalent tools for load and performance validation.

Work arrangement
Hybrid