At Honeywell, I work on building an AI-driven Industrial Operations Intelligence Platform that helps manufacturing teams transform operational data into actionable insights. My role focuses on designing scalable full-stack systems that combine modern web technologies with AI-enabled data processing.

I developed high-performance user interfaces using Next.js, React, and TypeScript, enabling analytics teams to visualize complex operational metrics and machine telemetry in real time. On the backend, I built microservices using Node.js and Express.js that process large volumes of industrial telemetry streams and securely integrate with internal analytics systems.

To enhance the platform’s intelligence capabilities, I implemented LLM-powered retrieval pipelines using OpenAI APIs and Pinecone, enabling contextual knowledge discovery from large operational datasets. I also containerized services using Docker and Kubernetes, improving deployment consistency and supporting scalable cloud infrastructure.

Additionally, I introduced reusable UI components through Storybook, reducing frontend development time by 31%, and implemented automated testing using Cypress and API validation frameworks, which helped decrease production defects by 24%.

At Cognizant, I contributed to building enterprise-grade digital platforms that improved customer service operations for large organizations. I worked closely with cross-functional teams to develop scalable applications that supported high-volume user interactions and complex service workflows.

On the frontend, I built interactive and responsive user interfaces using React.js, TypeScript, and Redux Toolkit, helping deliver seamless digital experiences across enterprise customer service portals. I designed modular components and optimized application performance, which significantly improved page load times and user interaction efficiency.

For backend services, I developed APIs using Python and FastAPI to orchestrate customer service workflows and enable reliable communication across distributed systems. I also designed GraphQL APIs to provide flexible and efficient data retrieval for frontend applications.

I worked extensively with PostgreSQL to design relational schemas and optimize queries for high-volume transactional systems. Additionally, I helped deploy services on AWS (EC2, S3, Lambda) and built CI/CD pipelines with GitHub Actions and Docker, reducing deployment time by 34%.

Monitoring dashboards built using Prometheus and Grafana improved operational visibility and helped reduce incident resolution time by 27%.

At Dell Technologies, I worked on the Enterprise Device Management Portal, a platform used internally to monitor and manage large fleets of enterprise hardware devices. My focus was on building scalable web applications that enabled IT teams to track device health, configurations, and lifecycle data in real time.

I developed responsive and user-friendly interfaces using React.js, JavaScript (ES6+), HTML5, and CSS3, allowing operations teams to monitor device metrics and perform configuration updates through a centralized dashboard. On the backend, I built services using Node.js and Express.js that handled device telemetry ingestion, authentication workflows, and operational data processing.

I also developed RESTful APIs that connected frontend dashboards with backend microservices to support device lifecycle tracking and configuration management. For data storage, I designed relational schemas in MySQL to manage device inventory, logs, and operational metadata.

To improve system performance, I implemented Redis caching, which reduced API response latency and minimized repetitive database queries. I also introduced automated testing using Jest and API validation scripts, helping reduce production defects by 21%.