AI QA & Evaluation Lead
Indexed description
The successful candidate will be responsible for ensuring the reliability, consistency, security, explainability, and governance alignment of AI-generated outputs and AI-driven workflows.
This role is critical in maintaining enterprise trust, operational quality, and compliance standards across AI initiatives delivered to government and enterprise clients.
The ideal candidate must possess strong experience in enterprise quality assurance, automation testing, AI evaluation methodologies, and governance-oriented validation frameworks.
Requirements
AI Evaluation & Validation
- Design and maintain AI testing and evaluation frameworks
- Develop benchmarking datasets and output validation methodologies
- Evaluate AI-generated responses for consistency, accuracy, and reliability
- Define confidence scoring and quality measurement approaches
- Implement automated regression testing for AI workflows
- Monitor prompt performance and behavioural consistency
- Detect model drift and output degradation
- Validate multilingual AI outputs including Arabic and English content
- Ensure AI outputs align with enterprise governance standards
- Support auditability and traceability of AI-generated results
- Implement review and approval workflows for AI systems
- Support compliance validation activities for enterprise deployments
- Conduct AI security and prompt injection testing
- Validate protections against unsafe outputs and misuse scenarios
- Support secure AI deployment and operational practices
- Produce quality assurance reports and evaluation summaries
- Recommend improvements to prompts, workflows, and AI models
- Support continuous optimisation of AI solution quality
- Bachelor's degree in Computer Science, Information Systems, Software Engineering, or related field
- Minimum 5 years experience in enterprise quality assurance or software testing
- Experience with automation testing frameworks
- Experience evaluating AI-powered systems preferred
- Experience in enterprise or regulated environments preferred
- Enterprise QA methodologies
- Automation testing frameworks
- API testing
- Regression testing methodologies
- Test case development
- Large language model evaluation
- Prompt engineering concepts
- AI benchmarking methodologies
- AI governance and validation concepts
- Risk assessment concepts
- AI security testing
- Auditability and traceability principles
- Experience in enterprise AI initiatives
- Exposure to regulated industries
- Experience with bilingual AI validation
- Familiarity with enterprise governance frameworks
- Exceptional attention to detail
- Strong analytical thinking
- Structured problem-solving capability
- High quality and governance awareness
- Strong documentation and reporting capability
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