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