# Prathamesh More > Applied AI Engineer | Full-Stack LLM Applications & Multi-Agent Systems Location: Dallas-Fort Worth Metroplex, United States Profile: https://flows.cv/prathameshmore I’m a software and machine learning engineer who loves building end-to-end AI products. While I have an MS in Data Science and enjoy training models, my real passion is the engineering side of AI: taking LLMs out of Jupyter notebooks and turning them into reliable, scalable web applications. Recently, my work has heavily focused on orchestrating multi-agent systems and building production-ready RAG pipelines. Some of my favorite recent builds include a 5-agent system on AWS Bedrock that automates complex literature reviews, and "ReMind," a full-stack Next.js/Python application that gives AI temporal memory. My core stack: • AI & Data: Python, PyTorch, LLMs, RAG, DSPy, Vector Databases • Engineering: TypeScript, React/Next.js, FastAPI, Docker, AWS I’m currently looking for full-time Applied AI or Forward Deployed Engineering roles. If your team is building AI applications and needs someone who can handle both the ML and the infrastructure, let's connect! ✉️ prpmore@gmail.com ## Work Experience ### Applied AI Engineer @ Indiana University Bloomington Jan 2024 – Present | Bloomington, IN ► Architected and built a novel "source-first" Retrieval-Augmented Generation (RAG) system for a generative AI research platform, completely eliminating model hallucinations and guaranteeing 100% factual integrity by grounding LLM outputs in pre-verified sources. ► Slashed a critical data collection workflow from weeks to just hours by engineering a multi-stage automation tool using spaCy and LLMs, resolving a major project bottleneck and accelerating research output for a published academic paper. ► Developed and deployed interactive Plotly and Dash dashboards to visualize emerging semantic trends from 550+ academic publications, enabling researchers to dynamically explore complex topic models and word co-occurrence patterns. ### Machine Learning Engineer @ Dimensionless Technologies Jan 2023 – Jan 2023 | India ► Operationalized a high-frequency stock prediction model by architecting and deploying a complete, end-to-end MLOps pipeline on AWS SageMaker. The system featured a full CI/CD workflow for automated model retraining, versioning, and deployment to a low-latency API endpoint for real-time inference. ► Automated over 90% of manual data entry for a key enterprise client by building and deploying a multi-modal AI service on Azure that fused OCR and BERT-based NLP to intelligently extract and structure data from complex tender documents. ► Partnered directly with cross-functional client teams to translate ambiguous business needs into concrete technical requirements, manage the project lifecycle, and deliver production-ready NLP models. ### Full Stack Developer @ Benchmark Computer Solutions Pvt. Ltd. Jan 2022 – Jan 2022 | India ► Built and deployed a high-throughput, containerized RESTful API using FastAPI and Docker to serve a resume parsing model, architecting the system to handle thousands of concurrent requests for an enterprise-scale recruitment platform. ► Boosted entity extraction accuracy from 78% to 91% F1-score by fine-tuning and integrating a state-of-the-art Hugging Face Transformer model for Named Entity Recognition (NER), significantly improving the quality of automated candidate screening. ## Education ### Master of Science - MS in Data Science Indiana University Bloomington ### Bachelor of Engineering - BE in Computer Engineering K. J. Somaiya Institute of Technology ## Contact & Social - LinkedIn: https://linkedin.com/in/more-prathamesh - Portfolio: https://www.prathamesh-more.com/ - GitHub: https://github.com/Spidey13 - Portfolio: https://www.prathamesh-more.com --- Source: https://flows.cv/prathameshmore JSON Resume: https://flows.cv/prathameshmore/resume.json Last updated: 2026-04-16