AI-native QA Engineer

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

• 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

• Competitive compensation package aligned with experience


• Remote-first work environment


• 20 paid time off days plus U.S. holidays


• Access to a modern AI-driven technology stack


• High degree of autonomy and freedom to experiment with new tools and approaches


• Professional development and learning reimbursement support


• Fast-paced startup culture with strong engineering collaboration

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