Vighnesh Bheed

I was a key decision-maker and Full-Stack Engineer, driving technical and strategic initiatives. I led QMS-Edge, an AI-driven defect detection platform, optimizing architecture to cut costs by 72%. I introduced Rust for critical tasks, improving performance and reliability. I enhanced software quality with end-to-end testing and integrated Generative AI for efficiency. Beyond development, I mentored developers, managed sprints, refined agile processes, and fostered a culture of continuous improvement.

As a Full-Stack Engineer, I enhanced PXL-Ident, a white-label identity verification app, improving both frontend (React) and backend (Node.js). I strengthened security by refining authentication, securing sensitive data, and ensuring compliance. On the frontend, I optimized UI/UX for better usability and performance. Collaborating across teams, I streamlined workflows and improved efficiency, making PXL-Ident more secure, scalable, and user-friendly.

At Prospr, I built and managed scalable AWS server architectures, ensuring high availability and efficiency. Using Node.js, I developed and optimized backend services, implemented robust APIs, and handled complex business logic. I designed and optimized SQL databases for performance and scalability. Additionally, I improved system reliability, automated deployments, and ensured seamless cloud integration, contributing to a high-performance, scalable backend.

As a Full-Stack Developer, I built a dynamic research platform using Svelte, Canvas, and Node.js, optimizing UI/UX, real-time updates, and responsiveness. I developed a deep learning model in Python to classify and validate experiments, improving data integrity. On the backend, I integrated Neo4j, GraphQL, PostgreSQL, and Couchbase for efficient data handling. Leveraging Kubernetes and RabbitMQ, I ensured scalability and fault tolerance, creating an AI-powered, intelligent research system.