AI Software Test Engineer

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1. Role Overview:

Responsible for ensuring the quality, accuracy, reliability, safety, and performance of AI systems through data, model, functional, security, and automation testing.
Design and execute manual and automated tests, evaluate AI outputs, and contribute to continuous QA process improvement.

2. Key Responsibilities:

• Analyze requirements, specifications, and business documents to develop test plans for AI systems.
  
• Design test cases and test data, and execute AI testing activities.
  
• Perform data testing, functional testing, model evaluation, security, and safety testing.
  
• Conduct Smoke, Sanity, Regression, and System Testing.
  
• Develop and maintain automated test scripts/frameworks for AI testing.
  
• Evaluate AI-specific quality aspects, including hallucination, bias & fairness, and model accuracy.
  
• Prepare test reports and communicate testing results to relevant stakeholders.
  
• Support quality assessment during critical phases and before product release.
  
• Identify opportunities to improve testing processes, automation, and QA effectiveness.
  

Requirements

3. Requirements

• Bachelor’s/College degree in Computer Science, Information Technology, Software Engineering, Information Systems, or a related field.
  
• At least 2 years of software testing experience.
  
• Solid understanding of SDLC, STLC, and software testing methodologies.
  
• Knowledge of data testing, information security, and security testing.
  
• Basic understanding of AI/ML/LLM, AI development lifecycle, Prompt Engineering, and LLM behavior.
  
• Understanding of AI testing concepts such as Model Evaluation, Hallucination Detection, Bias & Fairness.
  
• Experience with Automation Testing and programming is preferred.
  
• Experience with AI evaluation tools such as DeepEval or RAGAS is a plus.
  
• Knowledge of API Testing, SQL, Performance Testing, and Jira is an advantage.
  
• Strong analytical, problem-solving, and debugging skills.
  
• Detail-oriented, responsible, proactive, and quality-focused.
  
• Good communication and collaboration skills; able to work independently and as part of a team.
  
• Willingness to learn new AI technologies and testing methodologies.