Sharad Jain
Data-driven solutions architect, AI/ML engineering expert.
About
Sharad Jain is an AI founder and seasoned data scientist with a track record of building intelligent systems at scale. As the founder of autoscreen.ai, he architects production-grade conversational AI, leveraging complex technologies like Retrieval-Augmented Generation (RAG) and multi-agent workflows to solve real-world problems. His entrepreneurial drive is backed by extensive experience at companies like Meta and Withjoy, where he led high-impact data science and engineering initiatives.
Education
University of California Davis, Graduate School of Management
University Institute of Technology, Bhopal
Work Experience
autoscreen.aiBengaluru
Founder
withjoy.comSan Francisco, CA
Growth Data Scientist
Meta (Facebook)Menlo Park, CA
Data Scientist
AutodeskSan Francisco, CA
Data Scientist
Tata Consultancy ServicesPune, India
Data Analyst
Skills
Open Source Activity
GitHub Contributions
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Projects
EcoHome Energy Advisor
Built AI-powered smart home energy optimizer with RAG pipeline, delivering personalized EV charging and solar power recommendations for significant cost savings.
Automated Review System
Architected automated review system using Orchestrator-Worker pattern with specialized Claude agents for scalable student evaluation and consistent assessment.
AI Customer Service Agent
Developed AI customer service agent integrating Cloud SQL, Vertex AI Search, and Google Search for comprehensive pet store support with robust error handling.
UDA-Hub Support System
Engineered production-ready multi-agent support system achieving 85.7% compliance, featuring intelligent routing and three-tier memory architecture for CultPass.
Financial Analysis Agent
Created financial agent coordinating 6 specialized tools for 10-K analysis, SQL queries, and real-time market data integration with automatic PII masking.
Travel Agent Review System
Built automated review system with domain-specific agents for travel itinerary creation, weather compatibility analysis, and ReAct-based revision.
SWIFT Transaction Processor
Developed SWIFT transaction system with parallel fraud detection and Evaluator-Optimizer pattern achieving robust message validation and efficient processing.
Production AI Model Compression Pipeline
Achieved 89.4% model compression (5.83MB to 0.62MB) and 70% speed improvement through multi-stage pipeline, enabling real-time mobile AI deployment.