Palivela Bhanu prakash

I’m a highly motivated AI Developer focused on building and shipping product features with AI-assisted coding tools like Cursor, GitHub Copilot, and Claude. I design LLM-powered workflows, debug AI-generated code for quality and functional logic, and integrate LLM APIs into applications that actually work.

As an AI Product Developer at Growthmate Infotech, I developed production-ready features that significantly accelerated development cycles. I implemented Retrieval-Augmented Generation (RAG) pipelines to improve contextual accuracy, built prompt engineering templates for better end-user interactions, and refactored AI-generated code to meet standards for safety, quality, and robustness. I also collaborated daily with remote teams using Git and Slack, and evaluated emerging AI models to reduce latency and enhance application performance.

Earlier, at MedtourEasy, I created Python-based automated data processing workflows for large-scale AI training datasets. I integrated LLM-based agents to automate routine diagnostic tasks, built secure RESTful APIs for healthcare system data exchange, and added monitoring scripts to track reliability and response times in real-time environments. As a Junior AI Applications Engineer at Octanet, I automated internal scripts with Python, designed prompt engineering workflows, supported responsible AI code reviews, and delivered prototypes while adapting to a remote, asynchronous environment.

In my projects, I built ORALXCHECK, a Python-based oral cancer detection system using machine learning for medical image analysis, including automated preprocessing, safety protocols, data encryption, and hyperparameter tuning for real-time performance. I also developed a resume parsing engine using Natural Language Processing (NLP) and LLM-powered matching logic to extract unstructured documents into JSON, complete with RESTful API endpoints, RAG-based context, and modular architecture for maintainability.