Rohit Singh Chauhan

Leadership and Enterprise Management

• Executive Team Leadership: Directing 60+ specialists, managing a multimillion-dollar portfolio across Fortune 500 companies and government entities in the U.S. and India.
• Strategic Project Delivery: Consistently delivering high-impact AI/ML solutions that meet rigorous enterprise and governmental standards.

FINCA AuRA (Automated Research Assistant)

• Recognition: Achieved top 5% product status in the AWS Pathfinder award with dedicated AWS funding.
• Technology: Engineered comprehensive system leveraging RAG, fine-tuned LLMs, agentic workflows, vector databases, and optimized prompting.
• Capabilities: Automated theory of change development, impact pathway identification, topic modeling, and experience-based directionality analysis.
• Team Leadership: Directed 12 or more specialized developers.

Clinical Study Scoring Index (Pharmaceutical Client)

• Innovation: Developed an automated analysis and scoring mechanism that standardizes clinical study protocol complexity.
• Implementation: Designed an optimized retrieval system with a RAG pipeline featuring fine-tuned LLM components.
• Team Scale: Led 15 or more technical specialists.

Gen AI Capability Development

• Client: Collaborated with the Ministry of Development of the North Eastern Region (DoNER) and the Communication Ministry team under Mr. Jyotiraditya Scindia.
• Solutions: Built comprehensive governmental systems, including an advanced chatbot, a DPR analysis/approval platform, and an automated speech writer.
• Technology: Implemented Amazon Q, custom RAG architecture, agentic workflow systems, and human-in-the-loop verification.
• Team Leadership: Directed 12 or more implementation specialists.

Led strategic initiatives and technical teams to onboard and successfully deliver comprehensive solutions for key clients, significantly enhancing operational efficiencies and platform capabilities.

• LoanSi: Directed a team of six developers across Frontend, Backend, DevOps, and Mobile to architect, design, and deploy robust web and mobile applications for the operational management of field agents. Responsibilities included extensive client interaction for requirement gathering, detailed database schema and CRM design, and overseeing backend REST API development. Successfully deployed applications on AWS EKS using a GitHub Actions-based CI/CD pipeline, enabling load-balanced scalability. These technological enhancements positioned LoanSi as India's second-largest gold loan DSA platform, improving operational efficiency by 70% within six months.
• MakeMyPath: Independently conceptualized, developed, and deployed a proprietary machine learning algorithm (patent pending) designed for automated and personalized study path planning. The algorithm analyzes historical and real-time user data to dynamically calculate student performance metrics, such as accuracy progression, Bloom's taxonomy alignment, ideal versus actual time allocations, and overall platform engagement. Designed the database schema to effectively capture and standardize diverse user activities, continuously retraining the model to reflect evolving user patterns, and optimize exam preparation strategies.

• Solo effort as data engineer to deploy machine learning models into production. Data pipeline included following items:
• RabbitMQ messaging: RabbitMQ exchanges were setup to send messages into asynchronous queues in python, which were used to interact with legacy .Net application, for both receiving and sending messages.
• MongoDB Database: Once message was received to fire a model, python program picked data from MongoDB database based on complex query structure to filter out various reconciliation elements required by each ML model.
• OOPS code structure: The overall python codebase of approx. 30,000 lines was structured into various OOPs modules so as to increase reusability, decrease code redundancy, write better exception management and errors handling.

Worked primarily on model conversions, code optimization, machine learning, and legacy system migrations. Successfully converted BASEL regulatory models for 11 global portfolios, significantly reducing execution times from hours to minutes, and enabling substantial cost savings by migrating from expensive legacy systems to open-source, cloud-based technologies. Developed automated CI/CD pipelines for seamless deployment, cutting testing durations dramatically.

Additionally, I led teams in redesigning Internal Loss Data (ILD) tools into a streamlined, real-time, interactive R-Shiny dashboard deployed on AWS EC2. Reduced analytics processing time from 4 hours to just 2.5 minutes, significantly enhancing user experience and operational efficiency through improved data handling, real-time analytics, and robust automated error detection and logging systems.