Senior Software Engineer

Designed and built an AI-powered healthcare platform using React for the frontend and Python with Django for the backend, storing and deploying on AWS.
– Developed a full-stack web dashboard within Amazon Health to support a modular care planning system, enabling clinicians to create and manage patient-specific treatment plans.
– Implemented and maintained secure, high-performance RESTful APIs in Python for features like patient intake, billing, self-scheduling, and WebRTC-based video meetings in Node.js.
– Wrote and optimized complex SQL queries in Python and aggregation pipelines to handle large-scale data operations with low latency.
– Integrated OpenAI and LangChain into backend workflows to automate patient conversations in AI voice agents and virtual assistants by using Python and FastAPI.
– Handled real-time event processing and messaging at scale using Kafka and Redis, ensuring data consistency across distributed services.
– Ensured authentication and authorization using OAuth2 and AWS IAM, following HIPAA-compliant security practices.
– Built infrastructure with Terraform and CloudFormation, and deployed containerized microservices using Docker and Kubernetes (EKS).
– Monitored backend performance and data pipelines with DataDog and Splunk, proactively resolving anomalies. Implemented automated workflows using AWS Lambda and used S3 for secure file storage.
– Wrote unit and integration tests using Junit and Jenkins, mocking API responses from EHR.
– Mentored junior developers across remote and distributed teams, managing effective collaboration across time zones.

– Developed and launched booking features using Python with Django for backend services and React for the frontend, delivering a smooth and reliable booking experience.
– Designed scalable microservices in Python to handle core travel workflows, policy rules, and expense processing.
– Built and maintained GraphQL APIs and internal services for bookings, payments, and user data, ensuring high availability and performance.
– Improved API speed and efficiency by adding Query batching and Caching, reducing response times significantly.
– Delivered user-facing frontend features in React, including admin dashboards and real-time trip tracking for enterprise clients.
– Enabled real-time updates through WebSocket integrations and background processing using job queues. Integrated Elasticsearch with PostgreSQL to support fast, accurate full-text search while keeping relational data consistent for analytics.
– Used Kafka for the synchronization between PostgreSQL and ElasticSearch.
– Deployed cloud infrastructure using Google Cloud Platform tools like Compute Engine, Cloud Storage, and BigQuery for scalability and security.
– Set up thorough testing workflows with Testify (unit tests), Postman (API testing), and Playwright (end-to-end testing).
– Deployed services with Docker and Kubernetes, and managed infrastructure changes using Terraform and GitHub Actions CI/CD pipelines.