Developed and Architected an AI-powered RAG Chatbot application for individuals with anxiety disorders as a part of research work. The application had features like user-authentication, real-time notifications, and interactive metrics visualization with dynamic graphs.
Also worked on deploying LLMs locally on GPU-servers and working with AI frameworks like LangChain for building AI-driven applications. Additionally, built data and image annotation tools using Next.js, React Forms, and MongoDB to assist PhD students and professors in collecting high-quality datasets for AI/ML research work.
Associate Software Engineer
Accenture
Sept 2021 - June 2023
Developed microservices using Test-Driven Development with Maven, Java, Spring Boot and JUnit. Integrated third-party APIs such as Twilio and Microsoft EWS API for sending emails and notifications.
Optimized REST APIs performance by reducing latency from 295ms to 85ms through Redis caching. Additionally, documented it using Swagger, ensuring clear API specifications for integration and usage
Implemented observability using the LGTM (Loki, Grafana, Tempo, Prometheus) stack for centralizedlogging,metrics, and distributed tracing, which improved system monitoring, troubleshooting, andperformance analysis by monitoring application performance using Grafana dashboards.
Collaborated with automation team in writing scripts and CRON jobs for generating automated reports about health hecks of applications which helped management in keeping track of SLAs. These were deployed on AWS EC2 and monitored using AWS Cloudwatch.