Rahul Puri

Architected and deployed production-grade Python REST APIs and inference microservices on Azure App Service, sustaining sub-200ms latency across multi-tenant traffic. Implemented automated ML evaluation and QA testing pipelines with structured logging, guaranteeing reliability and inference performance across 30+ deployed model classes.

Designed an enterprise-grade document intelligence automation engine utilizing GPT-4 and FastAPI, slashing processing turnaround time from 3 days to under 18 hours (40% reduction). Developed robust downstream API integration layers to feed structured LLM outputs directly into client-facing enterprise software with schema validation and error fallback mechanisms.

Engineered an end-to-end Legal AI Retrieval system featuring a fine-tuned Llama 3.1 8B model and FAISS-powered semantic vector search for precise RAG contextualization. Delivered 5+ production-grade AI automation pipelines integrating LLMs, vector stores, and external REST APIs for enterprise clients.

Engineered an AI-driven meeting assistant orchestrating speech-to-text APIs and LLM-based summarization into automated downstream workflow engines. Developed complex multi-modal generative pipelines chaining text generation, image models, TTS, and FFMPEG video rendering through custom Python automation scripts.

Bachelor of Science in Computer Science from Sukkur Institute of Business Administration, completed in 2023.