AI-nativeQAEngineer

## Accountabilities In this role, you will design and evolve AI-powered QA systems that enhance automation coverage, improve defect detection, and strengthen release confidence across AI-driven products. Build and maintain AI-powered QA frameworks that automate test design, test execution, and validation workflows using LLM-assisted tools and modern automation stacks Develop automated test suites for functional, regression, integration, and performance testing across complex agent-based systems Use LLMs (such as GPT, Claude, and similar models) to accelerate test generation, bug analysis, and workflow validation Analyze defects and production incidents, identify root causes, and implement preventive testing strategies to reduce regressions Integrate automated testing pipelines into CI/CD workflows to ensure continuous quality validation Collaborate with engineering and product teams to define test strategies and ensure robust release validation Improve QA processes, expand test coverage, and enhance automation efficiency across evolving systems Requirements: The ideal candidate is a hands-on QA engineer with strong automation expertise and proven experience using AI tools in real testing workflows. 3+ years of QA experience, including at least 2+ years in test automation roles Proven hands-on experience using LLMs (GPT, Claude, Llama, or similar) in QA workflows and automation pipelines Strong programming skills in Python with expertise in PyTest and test automation frameworks Solid understanding of REST APIs, client-server architecture, and web service testing Experience working with SQL databases such as PostgreSQL or ClickHouse Familiarity with CI/CD pipelines and automated testing integration Strong analytical thinking and ability to work independently on complex systems and logic Ability to work aligned with EST time zone requirements Benefits: Competitive compensation package aligned with experience Remote-first work environment 20 paid time off days plus U.S.