AI Native QA Engineer

Quality Engineer

We are seeking a forward-thinking Quality Engineer to join our engineering team. This role centers on leveraging AI, automation, and modern quality engineering practices to ensure product quality at scale. The ideal candidate combines strong testing fundamentals with the ability to use AI-powered tools and workflows to accelerate test creation, execution, analysis, and continuous quality improvement. If you thrive in a fast-paced, AI-driven engineering environment and are passionate about building quality into every stage of the software lifecycle, we’d love to meet you.

Responsibilities:

AI-Assisted Test Engineering: Design, build, and maintain automated test suites for web, mobile, API, and AI-powered applications using modern automation frameworks and AI-assisted development tools.

AI-Powered Quality Assurance: Leverage AI tools and agents to generate test cases, identify edge cases, analyze failures, improve test coverage, and accelerate defect discovery while maintaining human oversight and validation.

CI/CD & Continuous Quality: Integrate automated quality checks, test execution, and AI-driven quality gates into continuous integration and delivery pipelines to enable rapid and reliable releases.

Test Strategy & Planning: Collaborate with product, engineering, and design teams to define risk-based testing strategies, quality objectives, and coverage plans using an automation-first and AI-enhanced approach.

Defect Analysis & Root Cause Investigation: Identify, document, triage, and verify defects while utilizing AI-assisted analysis tools to accelerate root cause identification and resolution.

Quality Intelligence & Reporting: Build dashboards and reporting mechanisms that provide insights into test coverage, defect trends, release readiness, automation effectiveness, and overall product quality.

AI & LLM Quality Evaluation: Develop and execute testing strategies for AI-enabled features, including prompt validation, output evaluation, hallucination detection, safety checks, and model behavior verification where applicable.

Tooling & Framework Innovation: Evaluate, adopt, and optimize modern testing frameworks, AI quality tools, and engineering workflows that improve team productivity and product reliability.

Quality Advocacy & Enablement: Promote AI-native quality engineering practices, mentor team members on automation and AI-assisted testing techniques, and foster a culture of continuous improvement and engineering excellence.

Continuous Learning & Experimentation: Stay current with emerging AI, automation, and quality engineering trends, continuously experimenting with new tools and approaches that can improve quality outcomes.

Qualifications

Bachelor’s degree in Computer Science, Engineering, or a related field.

Minimum of 3 years of experience in software quality assurance, test automation, or quality engineering.

Proficient in at least one modern programming or scripting language.

Hands-on experience with automation frameworks for UI, API, integration, and end-to-end testing.

Experience leveraging AI-powered development, testing, or productivity tools in day-to-day engineering work.

Familiarity with CI/CD practices, DevOps workflows, and automated quality gates.

Solid understanding of APIs, structured data formats, test data management, and system integration testing.

Knowledge of AI/LLM application testing, prompt evaluation, or AI quality assurance principles is a strong advantage.

Experience using version control systems, issue tracking platforms, and collaborative engineering tools.

Comfortable operating in Agile/Scrum environments and cross-functional product teams.

Strong analytical, problem-solving, and communication skills.

Demonstrated curiosity, adaptability, and willingness to embrace AI-native ways of working.