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AI Quality Assurance Engineer

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Onsite

AI Quality Assurance Engineer

VRINDA INTERNATIONAL

AI Quality Assurance Engineer

Skills

Testing & QAMachine LearningAI

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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