Building a scalable full-stack platform for over 150,000+ users to interact with custom-trained LLMs using AWS Bedrock, OpenSearch, and Llamaindex to handle user queries and generate AI-produced quizzes based on scraped course data.

Enhanced Milvus Vector Database by optimizing indexing and query execution for storing word embeddings, improving backend and search efficiency by 30%.

Programmed Python scripts for user authorization, monitoring, and API-based media management in DynamoDB and S3, serving over 2,500 user actions per minute and ensuring request schema validation for API Gateway events.

Achieved a 60% growth in the user base by developing in-app features such as podcasts, user connections, and a health tracker, leveraging React for the frontend and consuming REST APIs with Golang for backend integration.

Reduced screen load times by 30% through optimizing data rendering (images, 3D models/WebGL), incorporating AWS CloudFront for caching, and deploying efficient state management with ReactJS Hooks and Redux.

Designed and optimized gRPC services with custom middleware and interceptors, reducing service latency to 30%.

Developed and trained Deep Learning models for synthetic (AI based) image detection using a dataset of 1 million images on the Sol Supercomputer, utilizing visual pattern recognition technique to achieve a validation accuracy of 89%.

Developed a Docker image for the entire project and submitted it to the AI-FORCE Challenge.

Developed, and deployed microservices in Spring Boot (Java) for a leading apparel firm, enabling order pricing workflows and maintaining a scalable system architecture, resulting in a 35% decrease in payment processing time.

Elevated the accuracy of trend forecasting by 40% with the creation of Streamer and Server-Side Components for managing real-time data, incorporating Apache Kafka for enhanced forecasting of market trends and sales feeds.

Utilized Redis (Distributed Cache) as a middleware, accomplishing a 91% decrease in server response time and a 45% decrease in memory usage through integrated data compression techniques.

Drove a large-scale migration plan for the largest bank in the Middle East, transitioning on-premise systems to AWS using Python scripts. Leveraged AWS services such as S3, EC2, CloudFront, and RDS to build a high-availability infrastructure.

Designed and executed a project that achieved a 30% reduction in processing latency by implementing event-driven and asynchronous communication mechanism on message queues following Publisher-Subscriber (Pub/Sub) design patterns.

Achieved a 60% decrease in deployment time by designing User Interfaces (UI) and writing Bash Scripts for one-click deployment with HTML, CSS, and JavaScript, enhancing CI/CD pipeline orchestration in WebSphere (Linux) servers.

Collaborated with cross-functional teams in full development life cycle, end-to-end from design, implementation, and testing to documentation, for the client using Agile methodology overseeing facets of SDLC.

Devised a Progressive Web Application (PWA) in HTML, CSS, JavaScript, and ModelViewer for integrating AR models.

Utilized WebGL to showcase interactive 3D models, enabling users to rotate, zoom, and explore products.