VRINDA INTERNATIONAL
AI Quality Assurance Engineer
Skills
12 days ago
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Important information
Contract type:
Permanent
Location:
Delhi, India
Work mode:
Onsite
Published on:
16 October 2026
What they need
AI Quality Assurance Engineer
Summary We are seeking a dedicated professional to serve as an AI Quality Assurance Engineer within the IT Services sector. This pivotal role is responsible for ensuring the reliability, accuracy, and performance of artificial intelligence and machine learning applications. The position plays a critical part in the software development lifecycle by designing and executing rigorous testing strategies that validate AI models and their integration. The successful candidate will bridge the gap between technical development and quality assurance, guaranteeing that AI solutions meet high standards of functionality and user expectations while operating within the specified compensation range of ₹13-14 lpa.
Responsibilities
- Develop and implement comprehensive test automation frameworks specifically tailored for AI and ML-based systems.
- Conduct thorough functional and regression testing to verify that software behaves as intended across various scenarios.
- Create, maintain, and update detailed test documentation to ensure clear communication of testing processes and results.
- Perform in-depth root cause analysis to identify, isolate, and resolve defects within complex AI applications.
- Design and execute specific test cases focused on the unique challenges of AI/ML application testing.
- Validate system interfaces and data exchanges through rigorous API testing procedures.
- Execute test plans to ensure all software components meet the required quality benchmarks.
Requirements
Requirements:
- Proven expertise in test automation tools and methodologies.
- Strong background in performing functional and regression testing on diverse software platforms.
- Ability to produce high-quality test documentation and reports.
- Proficiency in conducting root cause analysis to troubleshoot complex technical issues.
- Specific experience in testing AI and Machine Learning applications.
- Skilled in the design, planning, and execution of detailed test cases.
- Competence in API testing and validation of system integrations.
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