Global Marketing & Digital Wealth QA Engineer

Planning 

• Understand requirements and Jira stories; create test plans, assess test automation feasibility, and estimate, schedule, and plan testing activities. 

• Use AI tools to analyze requirements and user stories, identify gaps or ambiguities early, and propose risk-based test coverage. 

Test Preparation 

• Analyze and understand scenarios and application flows, and prepare test scenarios and test cases for new functionality. 

• Prepare test data and manually execute test cases to understand application flows. 

• Use AI-assisted tools to generate and refine test scenarios, test cases, and synthetic test data, applying human review to validate accuracy and completeness. 

Test Execution 

• Execute new functional test cases for the current release, as well as manual and automated regression packs. 

• Log defects and retest fixed defects. 

• Apply AI to triage test failures, cluster related defects, and draft clear, reproducible defect reports. 

• Leverage AI-enabled visual, accessibility, and content checks to catch regressions across pages, markets, and devices. 

Test Scripting & Integration 

• Develop test scripts according to the BlackRock framework and perform dry runs of automation scripts. 

• Integrate automation with the CI/CD pipeline and complete a full run of automated scripts. 

• Use AI coding assistants (e.g., GitHub Copilot) to accelerate test script development, refactoring, and maintenance, including self-healing of brittle locators. 

• Help build reusable prompts, agent workflows, and standards that scale AI-assisted QA across the team, and measure their impact on coverage, cycle time, and defect leakage. 

User Documentation 

• Create and update user manuals. 

Core Skills: 

• Quality mindset with a development background. 

• Analytical mindset with the ability to grasp complex concepts easily. 

• Comfortable working in an agile environment, fluent in English. 

• Interested in continuously extending testing know-how. 

• Curious and pragmatic about AI—applies it to improve quality and speed, while exercising sound judgment on AI-generated output.