Kenneth Kibet

Bio

Computer Science graduate specializing in AI applications, machine learning, and backend software development. I build intelligent systems that combine large language models (LLMs), Retrieval-Augmented Generation (RAG), and modern web technologies to deliver accurate, reliable, and production-ready AI solutions.

My experience includes developing a Smart Classroom AI platform powered by a customized Qwen LLM with RAG, where I improved information retrieval, evaluated AI-generated responses for factual accuracy and relevance, and refined model performance through systematic testing. I have also built deep learning models using TensorFlow, including a CNN image classifier achieving 80–90% prediction accuracy, alongside REST APIs and backend services with Python and FastAPI.

Beyond AI development, I have professional ICT support experience working with Windows, Linux, networking, databases, and enterprise systems, giving me a strong foundation in troubleshooting, system reliability, and software deployment. I enjoy solving complex technical problems, evaluating AI systems, improving model quality, and building practical AI-powered applications that users can trust.