RAHUL S T

I’m a Generative AI Engineer Intern where I build end-to-end regulatory filing automation pipelines using Python, OCR, and LLMs. In my work at CampusPe, I extracted, validated, and formatted compliance documents, delivering a 45% reduction in manual processing time.

I focus on reliability, not just demos—integrating structured output parsing and prompt engineering for compliance-grade field extraction across regulatory workflows. As AI Developer 2, I owned the LLM integration layer, OCR pipeline architecture, and validation modules to ship production-ready workflows while reducing manual content effort by 35%.

Beyond my internship, I build practical ML and NLP solutions: a crop recommendation system reaching 95–96% accuracy, an AI-powered resume ranker with 80% matching accuracy, and a plagiarism detection system achieving 90% detection accuracy while reducing false positives by 25%. I’m currently strengthening my AI and data foundation through my B.E. in Artificial Intelligence and Data Engineering and ongoing AI/Data and technical learning, so I can keep turning real-world problems into measurable outcomes.