Introduction
watsonx Code Assistant is an exciting new offering from IBM that strives to revolutionize enterprise software development with Generative AI. We need your expertise, your motivation and your collaboration to take watsonx Code Assistant to the next level. As a QA engineer developer, you will be responsible for testing the microservices behind watsonx Code Assistant that interact with our Large Language Models.
Your Role And Responsibilities
- Design and develop test cases and perform test execution to meet high quality standards and key milestones.
- Design and develop automation test scripts, maintain and enhance the automation framework.
- Work with development team to debug/verify the defects and drive resolutions.
- Test results analysis, reporting and tracking.
- Identify concerns and potential problem areas.
- Think creatively to improve team productivity and efficiency
- Seek out innovative ideas & make recommendations upon evaluation and exploration of new tools and processes.
- Ensure effective and optimal administration & evolution of existing tools.
Preferred Education
Bachelor's Degree
Required Technical And Professional Expertise
- 8+ years experience
- Experience in Python programming and testing
- Experience in API testing using Pytest or similar testing framework
- Experience in UI desktop Automation
- Basic OS administration including Linux and Windows.
- Some knowledge of Database
- Ability to work in a fast paced environment working on multiple parallel releases.
- Ability to work in a globally distributed teams, and communicate effectively with remote developers and engineering team members
- understanding of continuous integration, software development process and cycles
- understanding of QA methodology, software development process and cycles
Preferred Technical And Professional Experience
- Exposure to testing a Gen AI product like a coding assistant
- Some experience of test frameworks such JUnit, Rational Functional Tester, etc.
- Experience with AI / ML models and evaluation techniques, including Large Language Models
