• Boosted new feature development efficiency by 30% by refactoring core Python services using FastAPI and Pydantic, reducing unit-test generation time by 60% through robust type validation and scalable architecture. • Collaborated with global cross-functional teams to design and deploy multi-user Virtual Machine solutions utilizing KVM and SR-IOV, enabling localized LLM processing to expand access to education in underserved, low-connectivity areas. • Reduced deployment setup time by 50% by streamlining the assignment of monitors and USB hubs to Virtual Machines, using Linux system events and USB-hub detection algorithms.

• Led the development of Edge AI Camera Solutions by deploying real-time inference pipelines using OpenVINO, DLStreamer, and MQTT, simplifying deployment and significantly shortening time-to-market for key partners. • Defined the technical direction for a high-performing scrum team, fostering continuous learning, mentorship, and a collaborative culture to maximize productivity and deliver innovative solutions. • Led microservices architecture at global scale, designing containerized services for massive deployments while contributing to EdgeX’s open-source community and establishing industry best practices.

• Led the development of a scalable Smart City AI solution leveraging OpenVINO, DLStreamer, and EdgeX Foundry, enabling real-time multi-camera monitoring and incident analysis. • Architected scalable containerized microservices with Go and PostgreSQL, boosting system efficiency by 30% through optimized query performance and modularized video stream management. • Developed advanced edge computing applications using sensor fusion to integrate RFID, cameras, and IoT devices, enabling real-time insights, loss prevention, and operational efficiency improvements for enterprises. • Transformed localized edge deployments into cloud-native solutions using AWS services such as Lambda, API Gateway, and DynamoDB, enabling seamless cross-store insights and centralized management for large-scale retail operations. • Reduced computation times by 80% of existing open-source RFID processing libraries through software profiling and algorithm optimizations in Java.

• Increased inventory accuracy in retail stores from 65% to over 95% by building TLS-secured, MQTT-based RFID tracking systems, delivering data-driven insights for Fortune 500 clients like Levi’s. • Developed intuitive tools to manage firmware updates, troubleshoot issues, and debug devices across large-scale deployments, significantly improving operational efficiency and user experience.

• Automated real-time data visualization using D3.js and Socket.IO, delivering actionable insights for retail clients and showcasing innovative solutions at NRF 2015, reinforcing the value of real-time decision-making to prevent operational rust in data processes.

• Developed geospatial information systems and 3D terrain simulation software with advanced night vision capabilities for Department of Defense applications, delivering cutting-edge solutions for mission-critical operations.

Technologies used: