QA Automation Engineer

Posted 1ds ago

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Job Description

QA Automation Engineer building automated coverage for web applications, APIs, and backend services. Helping Nimble Gravity’s financial-institution clients adopt AI reliably.

Responsibilities:

  • Develop comprehensive test plans and test cases with developers for new features and enhancements.
  • Execute manual regression and integration testing to validate application behavior and release readiness.
  • Automate existing manual test suites with reliable, maintainable coverage.
  • Design, implement, and improve automated testing for web applications, APIs, and backend services.
  • Collaborate with developers to validate implementations, identify defects, and verify resolutions.
  • Evaluate completed work and provide QA approval for promotion through staging and production environments.
  • Identify quality risks, technical roadblocks, and test-coverage gaps early in development.
  • Perform API, functional, integration, regression, and performance testing.
  • Validate application data and backend processing through SQL queries and database analysis.
  • Investigate failures and unexpected behavior using application logs, cloud monitoring tools, and diagnostic information.
  • Advocate for automated testing at unit, API, integration, and end-to-end levels.

Requirements:

  • 5+ years of experience in Quality Assurance, with a strong focus on test automation.
  • Proficiency in at least one programming language such as Python, C#, or TypeScript.
  • Experience with browser automation frameworks such as Playwright, Cypress, Selenium, or similar tools.
  • Experience testing HTTP APIs using tools such as Postman or comparable API-testing solutions.
  • Experience with performance and load-testing tools such as JMeter.
  • Knowledge of unit-testing frameworks such as pytest, Jest, NUnit, or similar.
  • Strong SQL knowledge and experience using database tools such as Microsoft SQL Server Management Studio.
  • Familiarity with the AWS Console and services such as ECS, RDS, CloudWatch, and S3.
  • General understanding of cloud computing and microservices architectures.
  • Strong technical aptitude around web applications, APIs, distributed services, and client-server architectures.
  • Knowledge of professional software engineering practices throughout the SDLC, including source control, code reviews, build and deployment processes, testing, and production operations.
  • Strong analytical and troubleshooting skills across application, database, and cloud infrastructure layers.
  • Strong communication and collaboration skills with developers and other stakeholders.