Thomas Thoppil
Lead Applied AI Engineer, ZS Bangalore
Greater Bengaluru Area
6+ years of work experience
Jun 20266 mosPresent
On-site
• Designed and implemented a content-based document tagging system for major pharmaceutical clients, enhancing downstream analytics.
• Scaled an AI platform utilizing LLMs for content analysis, ensuring compliance with enterprise standards.
• Developed distributed GenAI systems with LangGraph and RAG, automating intelligence across 150K+ documents.
Aug 20242 yrs 4 mosPresent
Led end-to-end design and development of a distributed system processing 150K+ documents with GenAI, RAG, LangGraph, and Celery, enabling sentence-level analysis and large-scale automation. Designed, delivered, and scaled a content-based document tagging system across two major pharmaceutical clients, tagging 600 documents in 3 hours and replacing a manual, often-skipped process with automatic bucketing for downstream analytics. Scaled an AI platform serving multiple major pharmaceutical companies, leveraging LLMs for content analysis and validation against enterprise compliance standards. Developed an LLM-powered content verification system that improved classification accuracy, optimizing prompting strategies to cut response latency by 40%. Led a modernization initiative migrating monolithic architecture to microservices using FastAPI, improving performance and scalability for a growing user base. Hardened the platform with JWT-based authentication and role-based access control to protect sensitive client data. Recognized with the Client Impact Award for delivering high-impact product outcomes.
Jun 20242 yrs 1 moJun 2026
On-site
Jan 20222 yrs 8 mosAug 2024
Architected a semi-supervised ML solution (PU learning) that increased medical claims capture by 60%, improving market share accuracy and oncology targeting precision. Built an automated data enrichment pipeline on AWS that cut model inference runtime by 90% via optimized step functions, processing workflows, and quality reporting. Led cross-functional collaboration with data engineering and UI/UX teams to deploy enrichment solutions across multiple tumor areas in live production.
Jan 20222 yrs 6 mosJun 2024
Bengaluru, Karnataka, India
• Architected a semi-supervised ML solution (PU learning) that increased medical claims capture by 60%.
• Developed an automated data enrichment pipeline on AWS, reducing model inference runtime by 90%.
• Collaborated with data engineering and UI/UX teams to deploy solutions across multiple tumor areas.
Mar 202111 mosJan 2022
Hyderabad, Telangana, India
• Developed predictive maintenance models using sensor data to identify early equipment failure patterns.
• Implemented tree-based and time series models to forecast equipment trends, optimizing maintenance scheduling.
• Contributed to reducing downtime in industrial operations at Prudent Technologies and Consulting, Inc., a leading consulting firm in Hyderabad.
Mar 202111 mosJan 2022
Developed predictive maintenance models on sensor data (e.g. voltage fluctuations) to detect equipment failure patterns early and reduce downtime. Implemented tree-based and time series models to forecast equipment trends and optimize maintenance scheduling for industrial operations.
Jan 20205 mosMay 2020
Gurugram, Haryana, India
Mainly dealing with STIR products such as Fed fund futures, Eurodollar futures, SF1 and SF3 contracts. Learnt how to use trading patterns such as spreads and butterflies
Thomas’s AI Stack
Education
Bachelor of Technology, Mechanical Engineering
Shiv Nadar University
20164 yrs2020
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