Software Quality Assurance Tester
AllysAI | AI-Native Enterprise
IndiaFresher1d agovia LinkedIn
About the Role
This is a full-time remote role for a Software Quality Assurance Tester.
Key Responsibilities
- Design, execute, and document test plans and test cases for AI-driven and enterprise software solutions, ensuring they meet defined quality and performance standards.
- Perform functional, regression, and integration testing.
- Identify and track defects.
- Collaborate with product, engineering, and data science teams to clarify requirements and resolve issues.
- Analyze test results.
- Recommend improvements to testing processes.
- Contribute to continuous quality enhancements in AllysAI’s platform and client solutions.
- Create and maintain testing documentation.
- Participate in reviews to help uphold high-quality delivery across projects.
Qualifications
- Strong foundation in test execution, including designing, running, and documenting manual and automated test cases.
- Experience ensuring software quality, with practical knowledge of quality assurance methodologies and best practices.
- Proficiency in software quality assurance, including defect management, root cause analysis, and regression testing.
- Well-developed analytical skills for interpreting requirements, evaluating system behavior, and diagnosing issues.
- Familiarity with testing tools and frameworks (e.g., Jira or similar issue trackers, test management tools, and automation frameworks is a plus).
- Understanding of software development lifecycles (Agile/Scrum) and collaborative work with engineering and product teams.
- Strong written and verbal communication skills, with the ability to document findings clearly and communicate with technical and non-technical stakeholders.
- Ability to work independently in a remote setting, manage priorities, and meet deadlines across multiple projects.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
- Experience testing AI, ML, or data-intensive products in an enterprise environment is beneficial but not required.