Principal Qa Engineer

Autodesk Autodesk · Enterprise · Bangalore, India

This Principal QA Engineer role focuses on leveraging AI and Generative AI to transform software quality practices within a cloud-native environment. The role involves leading quality strategy, championing automation, and applying AI-assisted development tools across the software testing lifecycle. Key responsibilities include defining test automation strategy, mentoring engineers on AI-enabled QA methodologies, and building AI-native testing frameworks.

What you'd actually do

  1. Lead end-to-end quality engineering initiatives for cloud-native and distributed applications, including the adoption of AI-driven quality engineering practices
  2. Define and drive the overall test automation strategy across UI, API, integration, and backend systems
  3. Design, develop, and maintain scalable, reusable, and reliable automation frameworks
  4. Collaborate with global cross-functional teams to deliver high-quality solutions
  5. Establish and continuously improve QA processes, standards, metrics, and best practices across teams

Skills

Required

  • 9+ years of experience in Quality Engineering or Software Testing
  • 3+ years in a technical leadership role
  • Designing and scaling automated testing solutions across UI, API, backend, and microservices architectures
  • Frameworks such as Playwright, Cypress, PyTest, REST Assured, or equivalent
  • Programming/scripting languages such as Java, JavaScript, or Python
  • API automation frameworks such as REST Assured, Cucumber, or similar tools
  • RESTful APIs, distributed systems, microservices architecture, and cloud-native technologies
  • Containerization and orchestration technologies such as Docker and Kubernetes
  • Testing applications hosted on cloud platforms including AWS, Azure, or GCP
  • CI/CD pipelines and tools such as Jenkins, GitLab CI, or GitHub Actions
  • Performance, scalability, and load testing methodologies and tools
  • Building AI-native testing frameworks or autonomous testing solutions
  • Proven ability to drive AI adoption initiatives and influence modernization of QA practices leveraging tools such as GitHub Copilot, Claude, Cursor, ChatGPT, or equivalent AI engineering platforms for test development and productivity acceleration
  • Agile/Scrum development methodologies
  • Analytical, problem-solving, communication, and stakeholder management skills
  • Ability to influence engineering practices and drive quality initiatives across teams

Nice to have

  • Experience implementing quality engineering practices for SaaS platforms
  • Familiarity with AI governance, responsible AI practices, and testing AI/ML-enabled applications
  • Observability and monitoring tools such as Grafana, Prometheus, or Datadog
  • Security testing and reliability engineering practices
  • Leveraging AI/ML-based testing solutions or intelligent test automation platforms

What the JD emphasized

  • AI-driven quality engineering practices
  • AI-assisted development tools
  • Generative AI
  • AI-native testing frameworks
  • autonomous testing solutions
  • AI adoption initiatives
  • AI engineering platforms
  • AI governance
  • responsible AI practices
  • testing AI/ML-enabled applications

Other signals

  • AI-driven quality engineering practices
  • AI-assisted development tools
  • Generative AI
  • AI-native testing frameworks
  • autonomous testing solutions
  • AI adoption initiatives
  • AI engineering platforms