Senior AI QA Engineer

Lahore, Punjab, Pakistan
Full Time
Quality Assurance
Experienced

Experience Required: 8+ Years
Employment Type: Full-Time
Work Mode: Hybrid
Location: Lahore / Karachi / Islamabad – Pakistan


Job Summary

We are looking for a Senior AI QA Engineer with 8+ years of experience in software quality assurance, test automation, and validation of AI/ML and data-driven systems. The role involves defining test strategies, building and maintaining automation frameworks, API testing, CI/CD integration, and end-to-end testing of AI and data pipelines.

The ideal candidate will work closely with Engineering, Data, ML, and DevOps teams to ensure high-quality, scalable, and reliable AI solutions in a fast-paced, collaborative environment.


Key Responsibilities

  • Define and execute test plans, test strategies, and test cases for AI/ML and data-driven applications
  • Design, develop, and maintain automated test frameworks using Selenium and Pytest
  • Perform API testing for RESTful services
  • Validate data pipelines, ETL workflows, and ML model outputs
  • Conduct end-to-end testing across the AI/ML lifecycle, including data ingestion, model training, inference, and deployment
  • Integrate automated test suites into CI/CD pipelines
  • Perform regression, integration, system, and performance testing
  • Identify, document, prioritize, and track defects through resolution
  • Collaborate closely with Data Engineers, ML Engineers, and DevOps teams
  • Ensure adherence to QA standards, best practices, and compliance requirements
  • Provide guidance and mentorship to junior QA engineers when required

Required Skills

  • Strong experience in Software Quality Assurance
  • Test Planning and Test Strategy
  • Test Automation
  • Selenium
  • Pytest
  • Python
  • API Testing (REST)
  • CI/CD Integration
  • Data Pipeline Testing
  • AI/ML Pipeline Testing
  • Regression and Integration Testing
  • Defect Tracking and Reporting
  • Git / Version Control

Preferred Skills

  • ML model validation (accuracy, drift, bias)
  • Experience with cloud platforms (AWS, Azure, or GCP)
  • Docker and Kubernetes
  • Performance and Load Testing
  • Data Quality and Monitoring frameworks
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