Girishma Hemnani
Lead Technical Architect @CVS Health
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WORK HISTORY
Lead Technical Architect @CVS Health
Chicago, IL, US
EDUCATION
Dr. A.P.J. Abdul Kalam Technical University (AKTU), Lucknow
Bachelor of Engineering (B.E.), Computer Science
Johns Hopkins Whiting School of Engineering
Masters in Artificial Intelligence, Artificial Intelligence
ABOUT GIRISHMA HEMNANI
I’m a Technical Architect with 15 years of experience designing large-scale, enterprise software systems, now focused on Applied AI, Machine Learning, and Generative AI systems. My work brings together strong pre-AI engineering foundations and hands-on AI system development gained through a Master’s in Artificial Intelligence.I’m currently completing my Master of Science in Artificial Intelligence, where I’ve built end-to-end AI and ML systems as part of advanced coursework in applied machine learning, NLP, generative models, evaluation, and AI system design. These projects emphasized not just model training, but how AI operates in real systems such as data pipelines, metrics, evaluation loops, tradeoffs, and deployment constraints.Prior to specializing in AI, I spent over a decade leading and influencing technical architecture and platform design across application, data, and cloud ecosystems. My background includes designing robust, scalable architectures, defining technical reference architectures, automating platform standards, and partnering with engineering and data teams in highly regulated enterprise environments.While my industry roles have focused on architecting the platforms and systems surrounding AI, my graduate work has allowed me to go deep into modeling, experimentation, and applied AI workflows, enabling me to bridge the gap between AI research and production-ready systems.Core focus areas- Applied Machine Learning & Generative AI systems- NLP, transformers, and model evaluation- LLM-based architectures and AI workflows- ML platforms, MLOps, and production reliability- AI governance, privacy, and enterprise integrationToday, I operate at the intersection of AI engineering, system architecture, and real-world constraints.
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