Senior Software Developer with strong expertise in building scalable, full-stack applications using Python (FastAPI), React.js, and modern cloud platforms including AWS and Azure. Experienced in architecting backend services, designing intuitive user interfaces, and integrating AI-powered document processing solutions. Proficient in developing secure APIs, automating deployments with CI/CD pipelines, and ensuring product quality through unit and end-to-end testing. Known for taking ownership of complex features, mentoring team members, and delivering high-impact solutions in fast-paced, agile environments. Proven ability to drive effective cross-functional collaboration and translate technical challenges into scalable, production-ready applications.
Overview
5
5
years of professional experience
Work History
Senior Software Developer
Boston Scientific
Marlborough, Massachusetts
12.2024 - Current
PROJECT: PACE – Pricing and Contract Execution Platform
Spearheaded the development of a contract AI intelligence platform that automated end-to-end lifecycle management for pricing, compliance, and reconciliation.
Owned and delivered backend services, React-based UI components, and real-time notification workflows for an integrated enterprise contract system.
Developed ingestion pipelines using FastAPI and Azure Functions to process structured and unstructured contract, invoice, GPO, and customer data from Azure Blob Storage to CosmosDB.
Integrated OpenAI-based LLM workflows to extract structured metadata from PDFs, enabling automated and dynamic compliance validations.
Implemented a custom Impact Tracking engine to calculate revenue exposure from multi-rule violations and contractual exceptions.
Built GraphQL APIs (Ariadne) and corresponding React dashboards to visualize contract status, flagged violations, and GPO handling in real time.
Engineered reconciliation logic to identify mismatches across invoice, contract, and customer metadata using dynamic business rules.
Secured all services using OIDC-based authentication and Azure Key Vault for environment-sensitive credential management.
Led sprint reviews, release planning, and production deployments, including patching, monitoring, and performance tuning.
Achieved automated test coverage across backend and UI layers using PyTest and Selenium.
Managed Terraform-based infrastructure deployment and CI/CD pipelines via GitLab across development, QA, and production environments.
Project : Clinical AI – Intelligent PDF Extraction Platform
Architected and delivered a full-stack AI solution to extract structured clinical data from unstructured PDF documents.
Independently gathered requirements, proposed the tech stack (AWS EC2, SageMaker, Docker, React, Chakra UI), and led end-to-end implementation.
Designed intuitive Figma mockups and converted them into a responsive React frontend with dynamic PDF upload and response rendering.
Integrated OpenAI models via SageMaker to generate real-time metadata extraction based on uploaded clinical PDFs.
Engineered a secure FastAPI backend to receive files, trigger AI inference, and return structured results.
Containerized and deployed frontend and backend using Docker, hosted on AWS EC2 with IAM-secured access via Ubuntu and Putty.
Built robust token validation, error handling, and response formatting to ensure stability and production readiness.
Demonstrated the product through stakeholder demos and positioned it under the “Clinical AI” namespace for future expansion.
Delivered microservices for global credit risk exposure tracking using Django, FastAPI, and Node.js.
Engineered scalable APIs to support IFRS, BASEL, CCAR/RWA, and SCCL regulatory data workflows.
Implemented batch data pipelines using Apache Airflow and Node.js to process large-scale exposure and financial metrics.
Optimized backend performance with SQLAlchemy and PostgreSQL, ensuring high-throughput, low-latency data operations.
Leveraged and Dockerized services and configured CI/CD pipelines using Jenkins and Kubernetes to streamline deployments.
Applied test-driven development with PyTest, Mocha, and Chai to ensure ninety percentage test coverage across services.
Integrated AWS services (Lambda, S3) for secure file storage and asynchronous processing tasks.
Collaborated with product owners and business analysts to translate complex regulatory requirements into production-grade features.
Contributed to Agile ceremonies, user story breakdowns, and sprint planning via Jira for effective team delivery.
Spearheaded data driven microservice architecture enhancements, boosting regulatory compliance metrics delivery speed by 30% with new caching layer and API response optimizations using Redis and Nginx.
Software Developer
Little Paddington
Hyderabad, India
01.2020 - 11.2021
PROJECT: Sales Training Portal
Architected and led the development of a unified, AI-powered training portal to integrate learning content from ALM, PodBean, and Vimeo into a centralized, web and mobile-friendly platform.
Designed and built the frontend using React.js and Chakra UI, implementing dynamic filtering, featured video tagging, and real-time search across multiple content providers.
Integrated REST APIs from all three platforms, engineered secure token-based authentication flows, and handled auth token refresh for ALM prior to SSO enablement.
Suggested and collaborated on Figma-based UI design, implemented interactive hero sections, and optimized the portal for mobile responsiveness.
Developed a filter-driven search interface to allow users to explore videos, podcasts, and courses individually or combined.
Implemented a caching mechanism for performance optimization and reduced API call redundancy.
Delivered live client demos, gathered iterative feedback, and continuously improved the product in response to business needs.
Conducted knowledge transfer sessions, mentored incoming developers, documented all setup instructions, and managed Git repositories.
Containerized the frontend and backend apps with Docker, deployed them to AWS EC2, and configured IAM roles and secure access policies.
Built fail testing and validation efforts, including PyTest and Selenium-based UI automation, ensuring a smooth production rollout.