AI Native QA Engineer

The Quality Engineer joins the engineering team to build product quality into every stage of the software lifecycle. The role combines software testing fundamentals, automation, and AI-powered workflows to improve coverage, accelerate defect discovery, and support reliable releases across web, mobile, API, and AI-enabled products.

Responsibilities

• AI-assisted testing: automate web, mobile, API, AI apps; generate tests, analyze failures.
• CI/CD quality: integrate automated checks, test runs, and AI-driven release gates.
• Test strategy and planning: define risk-based objectives and coverage across product teams.
• Defect analysis/reporting: triage issues, investigate causes, track trends and release readiness.
• AI/LLM quality evaluation: test prompts, outputs, hallucinations, safety, and model behavior.
• Tooling and framework innovation: evaluate, adopt, and optimize testing tools and workflows.
• Quality advocacy and learning: mentor teammates, promote AI-native practices, explore emerging tools.
  
  

Required Qualifications

• Bachelor's degree in a related field and at least three years QA experience.
• Proficient in a programming language; hands-on UI, API, integration, and end-to-end automation.
• Experience using AI-powered development, testing, or productivity tools in daily engineering work.
• Familiarity with CI/CD, DevOps workflows, and automated quality gates.
• Understanding of APIs, structured data, test data management, and system integration testing.
• Experience with version control, issue tracking, collaborative tools, Agile/Scrum, and cross-functional teams.
• Strong analytical, problem-solving, and communication skills.
  
  

Preferred Qualifications

• Knowledge of AI/LLM application testing, prompt evaluation, or AI quality assurance principles.
• Curiosity, adaptability, and willingness to embrace AI-native ways of working.