Dayyan Shah

I’m an AI and backend-focused software engineer who builds scalable applications with Python, Kotlin, and Firebase, with hands-on experience in LLM-based systems like RAG pipelines. I’m motivated by performance and scalability, especially when shipping production-ready solutions in fast-moving startup environments.

In my internship at Joget, I developed and deployed RESTful APIs for seamless third-party integration, and I built AI-driven workflow plugins and automation agents to reduce manual intervention. I also optimized backend logic and automation pipelines to enhance scalability and lower processing overhead in production workflows.

I apply the same end-to-end mindset to my projects: DocuQuery-LLM improved answer relevance and reduced query latency by 30–40% using optimized chunking and retrieval with LangChain and LLM APIs. Grocify delivers real-time Firestore synchronization with offline persistence and voice-enabled interaction, while my machine learning work includes a CNN image classifier reaching 95.8% accuracy and demand forecasting that improved prediction accuracy by 15–20% through feature engineering and model selection.