Developed MCP servers enabling real-time and write-access functionality for GPT agents, reducing dependency on overnight data syncs

Built Python-based exporter tool to automate ingestion of data from 5+ internal repositories (e.g., Slack, Confluence, and Software Lifecycle Management tools) into vector databases for LLM-powered retrieval

Built interactive React.js interface implementing 6 learning modules (Identity, Rhythm, Alphabet, Numbers, Vocabulary, Proverbs) with rhythmic HCI mechanics

Integrated frontend with Ruby on Rails REST APIs, implementing efficient data fetching and Redux state management, reducing API calls by 37%

Optimized performance through code splitting and lazy loading, reducing initial load time by 64% (from 4.8s to 1.7s) across devices

Developed real-time rhythm recognition features enabling students to learn through African drumming patterns (Alphariddim/Numeriddim systems), achieving 95% accuracy

Implemented responsive design and progress tracking, increasing engagement metrics by 40% and completion rates by 35%

Conducted weekly office hours and code review sessions, helping students master SOLID principles and design patterns

Evaluated assignments focusing on MVC architecture, modularity, and test-driven development

Assisted Professor Amit Shesh in evaluating exams and providing detailed feedback on students' performance

Developed automated warehouse management features using Java and Spring Framework, reducing

Build distributed microservices with RESTful APIs handling complex logistics operations, improving system throughput by 8% across multiple warehouses

Optimized SQL database performance by 35% using indexing strategies and query optimization, enabling system to handle 3x peak loads during sales events

Implemented multi-threaded batch processing systems for inventory management, reducing processing time by 85% (from 4 hours to 35 minutes)

Mentored 2 junior developers and conducted code reviews to maintain code quality standards

Engineered cluster-picking algorithm using Java, optimizing warehouse picking paths and reducing order processing time by 42% through efficient route planning

Automated inventory validation with Python scripts, processing 50K+ SKUs daily and reducing discrepancies by 35% in cycle counting operations

Created real-time monitoring dashboards for warehouse operations using Spring and RESTful APIs

Contributed to 3 production releases impacting 100K+ daily warehouse operations