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TELOMERE β’ India
Role & seniority: Senior QA Engineer (4β6+ years in QA, software testing, or quality automation)
Automated testing: Cypress, Playwright, Selenium
AI/tools for QA: Claude Code, Cursor, Antigravity (and other LLM-based tools)
CI/CD, test envs, deployment practices
Monitoring: Sentry, DataDog (AI-powered alerting/triage)
Web apps: React/Next.js (preferred)
Additional: AI-driven static analysis, code coverage, anomaly detection
Build and maintain automated end-to-end test suites; leverage AI to speed development and catch edge cases
Define and manage test strategies for new features, focusing on rich E2E web experiences
Integrate AI-powered QA tooling into CI/CD, simulate user behavior, and drive broader test coverage
4β6+ years in QA/software testing or quality automation
Strong experience with automated testing frameworks (Cypress, Playwright, Selenium)
Demonstrated use of AI tools to accelerate QA (e.g., Cursor, Copilot, Testim, CodiumAI, Diffblue)
Familiarity with writing/maintaining automated tests for modern web apps (React/Next.js)
Deep CI/CD understanding, test environments, deployment practices
Analytical, debugging ability; proactive collaborator in fast-paced teams
AI agents for QA (auto-test authors, regression explorers, defect triagers)
Backend/API test automation (Postman, REST Assured)
Experience in healthcare or r
Build and maintain automated end-to-end test suites using frameworks like Cypress, Playwright, or Selenium, with AI assistance to speed up development and catch edge cases.
Define and manage test strategies for new product features with a focus on testing rich E2E web experiences.
Use AI tools like Claude Code, Cursor, Antigravity, etc to rapidly generate test cases from requirements, user stories, and code diffs. Leverage AI tools to speed up development, catch edge cases and improve accuracy of tests.
Integrate AI-driven static analysis, code coverage tools, and anomaly detection into CI/CD pipelines.
Use LLMs and agents to simulate user behavior for broader scenario coverage.
Continuously evaluate and implement AI-powered QA platforms to improve regression, smoke, and exploratory testing.
Collaborate with engineers on shift-left testing practices, pairing during development to catch issues early.
Monitor application performance, errors, and logs using tools like Sentry, DataDog, or equivalent β augmented by AI-powered alerting and triage.
Contribute to defining AI-first QA best practices, playbooks, and tooling standards across the team.
4β6+ years of experience in QA engineering, software testing, or quality automation.
Strong experience with automated testing frameworks (e.g., Cypress, Playwright, Selenium).
Demonstrated usage of AI tools to accelerate or enhance QA processes β such as Cursor, Copilot, Testim, CodiumAI, Diffblue, or custom LLM-based tools.
Familiarity with writing, maintaining, and optimizing automated tests for modern web applications (React/Next.js preferred).
Deep understanding of CI/CD, test environments, and software deployment practices.
Strong analytical and debugging skills β able to quickly identify root causes and work cross-functionally to resolve issues.
Proactive communicator who thrives in a collaborative, high-velocity environment.
Experience with AI agents for QA (e.g., auto-test authors, regression explorers, or defect triagers).
Familiarity with backend testing, including API-level test automation (Postman, REST Assured, etc).
Exposure to healthcare or regulated industries.
Knowledge of performance testing tools (e.g., k6, JMeter) or visual regression testing suites.