AI Quality Assurance Engineer
Read straight from TAWANTECH's careers page, verified 3d ago.Seekless can tailor your résumé to it.
Seekless can write your résumé for this posting first.
Before you apply
LocationRiyadh, Riyadh Province, Saudi Arabia
Typefull-time
SenioritySenior
Experience5+ yrs
DepartmentIT
Company size201–500 people
PostedOct 6, 2026 · 1mo ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
Bachelor's degree in Computer Science, Data Science, AI, Engineering, or a related field
5+ years of experience in QA, AI/ML testing, software testing, or data quality
Strong understanding of machine learning and AI lifecycle processes
Experience with Python and automated testing frameworks
Knowledge of SQL and data validation techniques
Experience with APIs, cloud platforms, CI/CD, and version control
Understanding of ML model evaluation metrics and model monitoring
Strong analytical, problem-solving, and communication skills
Skills
Python
SQL
APIs
CI/CD
version control
cloud platforms
Job Title: AI Quality Assurance Engineer
Experience: 5+ Years
Job Type: Full-Time
Job Summary
Responsible for ensuring the quality, reliability, accuracy, and performance of AI/ML solutions throughout the development lifecycle. The role develops and implements testing strategies for AI models, data pipelines, AI applications, and production deployments while ensuring solutions meet business, technical, security, and regulatory requirements.
Key Responsibilities
•
Develop and execute comprehensive QA and testing strategies for AI/ML solutions.
•
Validate AI models for accuracy, consistency, robustness, and performance.
•
Design test cases for machine learning models, AI applications, APIs, and data pipelines.
•
Perform data quality, data validation, and data integrity testing.
•
Test AI outputs for accuracy, bias, hallucination, reliability, and consistency where applicable.
•
Conduct regression, integration, functional, performance, and automated testing.
•
Establish quality gates and acceptance criteria for AI model deployment.
•
Monitor model performance and identify model/data drift in production.
•
Collaborate with Data Scientists, AI Engineers, Data Engineers, and Business stakeholders.
•
Automate testing processes and integrate QA activities into CI/CD pipelines.
•
Document defects, test results, risks, and remediation activities.
•
Support model governance, auditability, and compliance requirements.
Requirements
•
Bachelor’s degree in Computer Science, Data Science, AI, Engineering, or a related field.
•
5+ years of experience in QA, AI/ML testing, software testing, or data quality.
•
Strong understanding of machine learning and AI lifecycle processes.
•
Experience with Python and automated testing frameworks.
•
Knowledge of SQL and data validation techniques.
•
Experience with APIs, cloud platforms, CI/CD, and version control.
•
Understanding of ML model evaluation metrics and model monitoring.
•
Strong analytical, problem-solving, and communication skills.