QA engineer for AI agentic workflows (manual)

Описания нет

• Manually test and validate code changes generated by an agentic pipeline that listens to customer friction from chat and voice support channels and produces code fixes from transcripts
• Collaborate with cross-functional teams to test wide-ranging code changes
• Perform exploratory testing, design test scenarios, and maintain confidence in production releases

• Experience manually validating code changes and software behavior generated by automated or agentic workflows using customer support transcripts from chat and voice channels
• Ability to collaborate and communicate effectively across engineering and product teams
• Strong foundation in manual testing, exploratory testing, test case design, and end-to-end quality assurance across web, mobile, or backend applications
• Proactive, hands-on approach and ability to own functional quality end-to-end
• Ability to understand diverse application flows, identify edge cases, and perform comprehensive regression testing across complex multi-system environments
• Experience defining and executing detailed manual test plans for frontend UI changes, backend business logic, and API behavior, using tools such as Postman or browser developer tools
• Strong product sense and customer empathy to evaluate software behavior against real-world user friction and support scenarios
• Ability to adapt manual test coverage in fast-paced, dynamic environments with rapidly iterating feedback loops
• Excellent issue-tracking skills, including writing clear, reproducible bug reports and working with developers to resolve root causes
• High attention to detail and focus on minimizing production bugs and user impact
• Будет плюсом: familiarity with test automation principles, scripting languages such as Python or JavaScript/TypeScript, or frameworks such as Playwright, Selenium, or Cypress; familiarity with AI/LLM-driven development workflows, agentic pipelines, or prompt-based code generation; experience analyzing support transcripts, customer service logs, or NLP outputs; exposure to CI/CD pipelines and continuous deployment workflows; background in event-driven architectures, microservices, or complex distributed systems

• 6–8 Hours of overlap with PST