I’m a full-stack and cloud-focused software engineer with a strong foundation in backend systems, DevOps, and machine learning. With experience in both enterprise and startup environments, I specialize in building scalable, production-grade systems using modern cloud and data technologies.
- Languages: Java, Python, JavaScript, TypeScript, Bash, Go
- Frontend: React.js, HTML/CSS, Material UI, MobX, Storybook
- Backend: Node.js, Express.js, Spring Boot, REST APIs, Microservices
- Cloud & DevOps: AWS (Lambda, EC2, API Gateway, CloudWatch, S3, DynamoDB), GCP (GKE, Artifact Registry), Jenkins, Docker, GitHub Actions, Terraform, CloudFormation
- Databases: MongoDB, MySQL, PostgreSQL, DynamoDB
- Testing: Selenium, Jest, Postman, TestNG, JUnit, Cypress, Karate, Cucumber BDD
- Methodologies: Agile, Scrum, TDD, BDD
- Modernized legacy systems and implemented CI/CD pipelines using Jenkins.
- Automated log analysis for performance optimization and enhanced monitoring.
- Designed RESTful APIs and optimized backend analytics for a healthcare claims platform.
- Enhanced system throughput with MongoDB and Express.js optimizations.
- Built insurance plan management systems and explored blockchain POCs using Solidity & Hyperledger.
- Delivered end-to-end full stack apps using React, Spring Boot, and AS400 mainframe systems.
- Built ML pipelines to predict Sepsis, CKD, and Heart Failure using MIMIC-IV ICU data.
- Engineered 41+ clinical features, applied SHAP for model explainability, and ensured end-to-end automation.
- Cloud-native app using Lambda, EC2, DynamoDB, S3, API Gateway for serverless ordering.
- Provisioned via CloudFormation, integrated real-time alerts with SNS and logs via CloudWatch.
- Visualized Java class dependencies (inheritance, composition) using React Flow.
- CI/CD with Docker, deployed with TDD approach to ensure high code quality.
- Built and deployed Flask microservices on GKE using Terraform and GitOps.
- Automated builds using Cloud Build and Artifact Registry, enabling seamless rollout across environments.
- Built a digit classifier using CNN on MNIST with OpenCV integration for real-time input.
-
restaurant-ordering-system
Serverless ordering backend on AWS with full infra automation. -
paedd-icu-prediction
Clinical ML pipeline to detect ICU diseases with SHAP explainability. -
software-dependency-visualizer
Dynamic code visualization for large-scale Java applications. -
kubeflow-microservices
GitOps-based multi-container system deployed via GKE and Terraform.
Currently diving deep into:
- 🔍 Retrieval-Augmented Generation (RAG) with LangChain & FAISS
- ☁️ Advanced AWS (Textract, SageMaker, VPC, CI/CD)
- 📊 MLOps & Data Engineering Best Practices
- 📚 Secure & Scalable Full-Stack Systems
Thank you for visiting my profile!
Feel free to connect, collaborate, or reach out for projects, mentorship, or tech chats. 🙌