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.
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- 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.
Required education
Bachelor's Degree
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
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IBM Software infuses core business operations with intelligence-from machine learning to generative AI-to help make organizations more responsive, productive, and resilient. IBM Software helps clients put AI into action now to create real value with trust, speed, and confidence across digital labor, IT automation, application modernization, security, and sustainability. Critical to this is the ability to make use of all data, because AI is only as good as the data that fuels it. In most organizations data is spread across multiple clouds, on premises, in private datacenters, and at the edge. IBM's AI and data platform scales and accelerates the impact of AI with trusted data, and provides leading capabilities to train, tune and deploy AI across business. IBM's hybrid cloud platform is one of the most comprehensive and consistent approach to development, security, and operations across hybrid environments-a flexible foundation for leveraging data, wherever it resides, to extend AI deep into a business.
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