AI-native QA Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI-native QA Engineer based in the United States.

This role sits at the intersection of quality engineering and modern AI systems, where testing is no longer just validation but an intelligent, automated, and continuously evolving process.
You will design and build AI-augmented QA frameworks that leverage LLMs to accelerate test creation, bug detection, and regression coverage.
The work is highly technical, combining automation, backend validation, and AI-driven workflows to ensure product reliability at scale.
You will collaborate closely with engineering, product, and research teams to validate fast-moving releases in a high-velocity environment.
The role emphasizes ownership, experimentation, and the ability to turn complex systems into robust and testable architectures.
You’ll be expected to integrate tools like LLMs into daily QA operations, fundamentally reshaping how quality is engineered.
This is a hands-on, high-impact position within a fast-growing AI-native organization.

You will be responsible for building and evolving AI-powered QA systems that ensure product quality across complex, fast-changing workflows. Your role will combine automation engineering, testing strategy, and AI-driven experimentation.

• Design and build AI-assisted testing frameworks and pipelines covering functional, regression, integration, and performance testing.
• Develop and maintain automated test suites integrated into CI/CD pipelines using modern engineering practices.
• Leverage LLMs and AI tools to generate test cases, analyze defects, and accelerate QA workflows.
• Perform root cause analysis of bugs and production incidents, identifying patterns and preventing regressions.
• Collaborate closely with developers, product managers, and R&D teams to validate releases and ensure system reliability.
• Improve test coverage, QA processes, and automation frameworks continuously through data-driven insights.
• Support validation of agent-based or AI-driven systems and ensure robustness of complex workflows.

Requirements

The ideal candidate is a technically strong QA engineer with deep automation experience and hands-on use of AI tools in real-world workflows.

• 3+ years of QA engineering experience, including at least 2+ years focused on automation.
• Proven hands-on experience using LLMs (e.g., GPT, Claude, Llama) as part of QA or engineering workflows.
• Strong programming skills in Python and experience with PyTest or similar frameworks.
• Solid understanding of REST APIs, client-server architecture, and distributed systems.
• Experience working with SQL databases such as PostgreSQL or ClickHouse.
• Hands-on experience integrating automated tests into CI/CD pipelines.
• Ability to work independently on complex systems and ambiguous business logic.
• Comfortable working in an EST timezone environment.

Benefits

• Remote-first work environment
• 20 days of paid time off plus U.S. holidays
• Access to a modern AI-first technology stack with freedom to experiment
• High-autonomy, fast-paced startup culture
• Professional development and learning reimbursement
• Opportunity to work on cutting-edge AI systems and agent-based platforms
• Collaborative and open engineering environment