Senior QA Engineer
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Key skills for this role
About the Role
VaporVM is seeking a Senior QA Engineer to lead QA strategies for Data & AI programs in Riyadh, Saudi Arabia. The role involves testing data pipelines, AI/ML models, GenAI/LLM applications, and Agentic AI systems.
Key Skills for This Role
Responsibilities
- Define and enforce QA frameworks, processes, and standards for data pipelines, AI/ML models, GenAI/LLM applications, and agent based AI systems
- Develop and automate data validation tests (integrity, consistency, lineage, schema drift)
- Design and execute ML model validation tests, including performance, fairness, bias, and reproducibility
- Implement automated prompt response validation for GenAI/LLM applications
- Integrate QA processes into CI/CD, MLOps, and LLMOps workflows
- Develop monitoring and alerting systems for data drift, model decay, and pipeline failures
- Define, track, and report on AI evaluation metrics
- Ensure compliance with AI governance, ethics, security, and privacy requirements
- Document QA processes, maintain reusable test cases, and support audits
Requirements
- 5+ years of experience in Quality Assurance
- At least 2+ years focused on Data, AI/ML testing
- Hands on expertise in testing LLM based applications and Agentic AI systems
- Strong foundations in data quality assurance and AI/ML model validation
Full Job Posting
Role Overview
- We seek a Senior QA Engineer to lead the design, testing, validation, and automation of QA strategies across our Data & AI programs.
- The role spans testing data pipelines, AI/ML models, Generative AI (LLM) applications, and multi agent (Agentic AI) workflows.
- The ideal candidate will bring hands on expertise in testing LLM based applications and Agentic AI systems, along with strong foundations in data quality assurance and AI/ML model validation.
Key Responsibilities
- Define and enforce QA frameworks, processes, and standards for data pipelines, AI/ML models, GenAI/LLM applications, and agent based AI systems.
- Develop and automate data validation tests (integrity, consistency, lineage, schema drift).
- Design and execute ML model validation tests, including performance, fairness, bias, and reproducibility.
- Implement automated prompt response validation for GenAI/LLM applications (semantic similarity, factuality, hallucination detection).
- Integrate QA processes into CI/CD, MLOps, and LLMOps workflows.
- Develop monitoring and alerting systems for data drift, model decay, and pipeline failures.
- Define, track, and report on AI evaluation metrics.
- Ensure compliance with AI governance, ethics, security, and privacy requirements.
- Document QA processes, maintain reusable test cases, and support audits.
Skills & Qualifications
- 5+ years of experience in Quality Assurance, with at least 2+ years focused on Data, AI/ML.
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