At PNC Bank, I work on building intelligent, scalable backend systems that power modern financial services. My primary focus has been developing an AI-driven financial assistant platform designed to automate customer support interactions and deliver personalized financial insights.

I led the development of backend services using Python and FastAPI, enabling highly responsive APIs that integrate with internal banking systems and data platforms. One of the key initiatives I contributed to was implementing a Retrieval-Augmented Generation (RAG) architecture using LangChain and FAISS, allowing the assistant to retrieve contextual information from large internal datasets and provide more accurate responses. This solution improved response accuracy and reduced manual support intervention by 45%.

I also worked on integrating OpenAI and Hugging Face models to create conversational interfaces capable of handling complex financial queries. On the infrastructure side, I deployed services on AWS using Lambda, S3, and API Gateway, which improved reliability and reduced infrastructure overhead by approximately 30%.

Additionally, I helped establish MLOps practices using Docker and MLflow, enabling better model versioning and monitoring.

During my time at Infosys BPM, I worked on designing and developing scalable enterprise applications focused on customer data integration and real-time processing systems. My work primarily involved building cloud-based platforms that unified customer data from multiple internal systems to provide a single, reliable source of truth.

I engineered a microservices-based data integration platform using Node.js and Express.js, enabling seamless data exchange across enterprise services. To support real-time data processing, I implemented event-driven architectures using Apache Kafka, which significantly improved system scalability and enabled near real-time updates across downstream applications.

On the frontend side, I developed dynamic UI components using React.js and Tailwind CSS, which improved the overall user experience and reduced page load time by approximately 35%.

I also containerized services using Docker and orchestrated deployments through Kubernetes, improving deployment consistency and reducing release cycles by 40%. To maintain high code quality, I implemented CI/CD pipelines using Jenkins and GitHub Actions along with automated testing using Jest and Cypress.

At Trigent Software, I contributed to the development of enterprise-grade applications focused on order processing automation and distributed system integration. I worked closely with cross-functional teams to design and implement scalable backend services that streamlined business workflows and improved operational efficiency.

One of my key projects involved building an order processing automation platform using Java and Spring Boot, designed to manage the end-to-end lifecycle of high-volume order transactions. I developed secure RESTful APIs to connect frontend applications with backend services, enabling reliable communication between distributed components.

To improve system reliability during high transaction volumes, I implemented asynchronous messaging using RabbitMQ, allowing services to process requests efficiently without impacting system performance. I also optimized database queries and indexing strategies in MySQL, reducing data retrieval latency by 25% and improving overall system responsiveness.

On the frontend side, I developed responsive UI modules using Angular and HTML5, which helped reduce manual processing efforts by around 30% for internal operations teams.