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QA Engineer
3 days ago
Please note you must be residing in BC and must show case AI project experience in your resume in order to be contacted.
QA Engineer - AI Experience - Augmented Development Process
Location: Vancouver Downtown / Hybrid 2 days onsite
MUST HAVE: Do you have experience or skills related to AI or machine learning applications as a QA?
Role Overview:
We are seeking a QA Engineer who is passionate about leveraging the latest in test automation and AI technologies to improve software quality. This is not your conventional QA role; it requires a deep understanding of modern QA methodologies, automation tools, and a keen interest in AI-augmented processes. You will play a pivotal role in shaping our AI-driven QA framework, ensuring that our software meets the highest standards of quality and reliability.
Key Responsibilities:
· Collaborate with cross-functional teams to understand product requirements and develop comprehensive test plans, test cases, and test scripts.
· Implement and maintain automated testing frameworks using a variety of tools and technologies, with a focus on efficiency and scalability.
· Work closely with the development team to integrate AI-driven testing methodologies into the software development lifecycle.
· Utilize JIRA and other project management and bug tracking software to manage test plans, cases, and report issues effectively.
· Continuously evaluate and incorporate new test automation tools and practices to enhance testing effectiveness.
· Participate in continuous learning opportunities to stay abreast of emerging AI and QA technologies and methodologies.
Qualifications:
· Bachelor's degree in Computer Science, Engineering, or a related field.
· Proven experience in QA engineering, with a strong background in test automation.
· Proficient with automation tools (e.g., Selenium, TestComplete, Jenkins) and scripting languages (e.g., Node, Python, JavaScript).
· Extensive experience with JIRA as a project management and bug tracking tools.
· Demonstrated ability to learn and adapt to new technologies and methodologies, particularly in AI and machine learning applications in QA.
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