QA Test Engineer - AI-Driven Automation (Hybrid)

New-York-Life

New York (NY)

Hybrid

USD 65,000 - 93,000

Full time

8 days ago
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Job summary

New York Life in New York City is seeking a detail-oriented QA Test Engineer to validate software applications, design and run test cases, and support automation across web, API, and backend workloads in a hybrid setting.

You will work with Selenium WebDriver, MABL, Cypress, Playwright, TestNG, JUnit, Rest Assured and Jenkins to improve coverage and reliability while applying AI-powered testing to boost efficiency.

Qualifications

  • Strong understanding of STLC and SDLC.
  • Experience in manual and automation testing.
  • Knowledge of Selenium, API testing tools, SQL, Agile, and CI/CD pipelines.
  • Experience with defect tracking tools such as JIRA and PractiTest.
  • Bachelor’s degree in computer science, Information Technology, or related field.
  • Basic to intermediate understanding of AI-assisted testing concepts.

Responsibilities

  • Develop and maintain automated test scripts for web, API, and backend applications.
  • Execute automated regression suites and analyze test execution results.
  • Support CI/CD integration for automated test execution.
  • Improve automation framework stability and reusability.
  • Work with Selenium WebDriver, MABL, Cypress, Playwright, TestNG, JUnit, Rest Assured, Jenkins.
  • Collaborate with Business Analysts, Developers, Product Owners and Scrum teams.

Skills

Selenium WebDriver
API testing
SQL
CI/CD
JIRA
PractiTest
AI-assisted testing
Jenkins

Education

Bachelor’s degree in CS/IT or related field

Tools

MABL
Cypress
Playwright
TestNG
JUnit
Rest Assured

Job description

New York Life in New York City is seeking a detail-oriented QA Test Engineer to validate software applications, design and run test cases, and support automation across web, API, and backend workloads in a hybrid setting.

You will work with Selenium WebDriver, MABL, Cypress, Playwright, TestNG, JUnit, Rest Assured and Jenkins to improve coverage and reliability while applying AI-powered testing to boost efficiency.

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