# VIHAS ADI > AI Engineer · Deep Learning & RAG Systems · Production LLM Pipelines · PyTorch · LangChain · AWS · M.S. AI @ Yeshiva University Location: Iselin, New Jersey, United States Profile: https://flows.cv/vihas https://vihasadi.github.io ## Work Experience ### AI Engineer @ Prevail Infotech INC, Sandy, Utah, US Jan 2024 – Present | Sandy, Utah, USA Architected and deployed an enterprise Knowledge Intelligence Platform using Retrieval-Augmented Generation (RAG), indexing 50K+ internal documents to enable natural language querying and automated knowledge retrieval across business units. • Designed and implemented end-to-end Generative AI workflows leveraging Large Language Models (LLMs) for enterprise automation, semantic search, and contextual Q&A systems. • Built RAG pipelines using LangChain, FAISS/Pinecone vector databases, and HuggingFace embeddings, improving contextual response accuracy by 25–35% through optimized chunking, retrieval tuning, and metadata filtering strategies. • Developed scalable document ingestion and preprocessing pipelines for unstructured data (PDFs, reports, internal knowledge bases), enabling semantic indexing and structured summarization. • Reduced hallucination rates by approximately 18% through retrieval re-ranking, prompt engineering refinements, and structured output formatting with validation checks. • Deployed containerized AI services via FastAPI and Docker on AWS EC2, handling 5K+ requests/day with sub- 300ms average retrieval latency and high system reliability. • Fine-tuned transformer-based models for domain-specific NLP tasks using parameter-efficient tuning techniques and iterative prompt optimization to improve domain alignment and inference performance. • Implemented monitoring and evaluation frameworks to measure retrieval quality, generation relevance, and system stability using automated metrics and human feedback loops. ### Machine Learning Engineer @ Next Cloudwave Solutions Pvt Ltd, Hyderabad, India Jan 2022 – Jan 2023 | Hyderabad, Telangana, India Led development of an enterprise retail demand forecasting system processing 1M+ historical transaction records to generate SKU-level weekly predictions for inventory optimization. • Designed and deployed scalable end-to-end ML pipelines from data ingestion and preprocessing to model serving using Python, scikit-learn, and SQL. • Built and optimized supervised learning models (classification & regression), improving predictive accuracy by 15–22% through advanced feature engineering and hyperparameter tuning. • Engineered robust data preprocessing workflows for large structured datasets (1M+ records), improving down- stream model stability and consistency. • Productionized ML models via RESTful APIs (FastAPI), enabling real-time and batch inference integration into client systems. • Automated model retraining and evaluation workflows, reducing experimentation time by approximately 30% and improving reproducibility. • Implemented performance monitoring, validation protocols, and A/B testing to continuously enhance inference quality and model reliability in production. ## Education ### Master's degree in Artificial Intelligence Yeshiva University ### Bachelor's Degree in Computer Science Teegala Krishna Reddy Engineering College ### Bachelor of Technology in Computer Engineering TKR College of Engineering Technolog ### Bachelor of Computer Science TKR College of Engineering Technolog ### Master of Science in Artificial Intelligence Yeshiva University ### M.S. Artificial Intelligence Yeshiva University ## Contact & Social - LinkedIn: https://linkedin.com/in/vihas-adi-009531294 - Portfolio: https://vihasadi.github.io - GitHub: https://github.com/Vihasadi --- Source: https://flows.cv/vihas JSON Resume: https://flows.cv/vihas/resume.json Last updated: 2026-04-16