Ejiaka Nwaeze

Senior QA Architect and M.Sc. Bioinformatics candidate with 10+ years of experience in high-stakes software validation. Specializing in the Evaluation and Safety of Generative AI/LLM systems, with a focus on clinical accuracy and bias detection. Expert in building automated frameworks for RAG pipelines, edge-AI (NVIDIA Jetson), and clinical data integrity. Proven track record of ensuring software reliability in complex medical and technical environments.

Senior QA & AI Evaluation Architect | QA mentor

• Led the transition from traditional QA to AI-driven testing, implementing automated validation for LLM-assisted workflows.
• Developed evaluation frameworks for RAG (Retrieval-Augmented Generation) systems, measuring faithfulness, relevancy, and context precision.
• Directed AI Red-Teaming efforts to identify edge-case failures in model reasoning and clinical data interpretation.
• Architected end-to-end automation suites that reduced regression testing time by 60% while increasing test coverage for ML-integrated modules.

Clinical Bioinformatics Specialist / Senior Analyst at Covenant university

• Applied bioinformatics expertise to validate Clinical AI models, ensuring 99.9% accuracy in diagnostic data processing.
• Managed data integrity for large-scale biological datasets, implementing strict QA protocols for medical laboratory software.
• Developed Python-based scripts to audit XGBoost and Random Forest models for biological proxy bias.

M.Sc. in Bioinformatics – Covenant University

B.Sc. in Medical Laboratory Science – Ebonyi state university