Lohith Kumar Neerukonda
Ai Software Engineer @Marvel Technologies Inc
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WORK HISTORY
Ai Software Engineer @Marvel Technologies Inc
Southfield, MI, US
Real-Time Inventory & Working Capital Optimization (Python, Azure)- Designed and deployed an end-to-end AI inventory optimization platform on Azure using Python, reducing projected overstock and stockout scenarios by automating demand forecasting and replenishment decisions across the supply chain- Built demand forecasting models using Prophet with external economic indicators and seasonal signals, improving forecast accuracy for multi-SKU procurement planning- Translated model outputs into actionable procurement rules using supplier lead times, cost constraints, and priority-based allocation logic supporting partial fulfillment and real-time inventory state- Implemented a financial reporting layer generating journal entries, balance sheets, and income statements directly from operational data, eliminating manual reconciliation- Engineered bulk ingestion pipelines processing Excel and CSV enterprise datasets with schema validation, error handling, and audit logging.
EDUCATION
Anil Neerukonda Institute Of Technology & Sciences
Bachelor of Technology - BTech, Information Technology
University of North Texas
Master's degree, Information Technology
ABOUT LOHITH KUMAR NEERUKONDA
Over the past 3 years I have worked across supply chain, real estate and fintech, building both AI-powered platforms and the backend infrastructure that makes them reliable and scalable in real business environments. Most AI engineers stop at the model. I go the full distance, from data preparation and forecasting to REST APIs, cloud deployment, and production monitoring.At Marvel Technologies, I designed and deployed an end-to-end inventory optimization platform on Azure that uses demand forecasting with external economic indicators to drive automated procurement and replenishment decisions. I also built the financial reporting layer, including balance sheets and journal entries generated directly from operational data.Before that, at Anywhere Real Estate, I integrated AWS Bedrock to automate property description generation from images, cutting manual effort for listing teams. At Infosys, I built device confidence and transaction risk scoring services handling high-stakes authentication flows in fintech, using Drools, Kafka, and circuit breaker patterns at scale.My technical core: Python for AI and data pipelines, Java and Spring Boot for backend services, Azure and AWS for cloud infrastructure. I hold a Microsoft Azure Developer Associate certification and a Master\'s in Information Technology from the University of North Texas.I am currently open to AI Engineer, Backend Engineer, or Full-Stack Engineer roles where I can keep building systems that connect intelligent models to real business outcomes. If that sounds like your team, I would love to talk.
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