QA Engineer - AI Native and Agentic Systems
New
Remote across India, US Pacific hours (4-8 hours overlap)Full-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 3+ years in QA (manual + automation)
- Required Skills
- Artificial IntelligenceCypressAPI testingSeleniumCI/CDPlaywright
Requirements
- 3+ years in QA (manual + automation)
- Strong understanding of SDLC
- Strong understanding of test strategies
- Strong understanding of failure modes in complex SaaS systems
- Hands-on experience with UI automation (Playwright / Cypress / Selenium)
- Hands-on experience with API testing
- Demonstrated use of AI in QA beyond basic test generation
- Experience with autonomous testing
- Experience with AI-assisted exploratory testing
- Experience with intelligent test orchestration
- Ability to explain how AI systems decide what to test next
- Experience designing QA frameworks or platforms (Strongly Preferred)
- Experience integrating QA into CI/CD at a system level (Strongly Preferred)
- Experience with Performance / reliability testing (Strongly Preferred)
- Healthcare or regulated systems experience (Strongly Preferred)
- Prior work where QA influenced architecture decisions (Strongly Preferred)
Responsibilities
- Design AI-based systems that explore UI, APIs, workflows, and edge cases without pre-defined scripts
- Generate and execute tests dynamically from product behavior
- Discover bugs through exploration, not just assertions
- Move beyond static automation into self-directed testing systems
- Build QA agents that continuously test features as development agents build them
- Provide structured, actionable feedback in real time
- Loop with development agents until quality thresholds are met
- Own the QA feedback loop as a first-class system, not a manual process
- Validate quality across web UI, backend services, APIs, data integrity, and end-to-end user journeys
- Automatically identify functional defects, workflow breaks, regression issues, performance and reliability risks
- Build systems that run continuously, adapt as the product evolves, and increase coverage automatically over time
- Define what “release-ready” means and block releases when quality is insufficient — with evidence
- Raise risks early, clearly, and decisively
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