AWS Certified Developer Associate with 2+ years of experience designing and implementing scalable applications, data pipelines, and cloud-native solutions. Currently SDE at GE HealthCare working on healthcare data platfo…
AWS Certified Developer Associate with 2+ years of experience designing and implementing scalable applications, data pipelines, and cloud-native solutions. Currently SDE at GE HealthCare working on healthcare data platforms, RAG-based AI services, containerized microservices and DevOps automation with Terraform/AWS CDK. Proficient in Python, FastAPI, CI/CD, Docker, AWS, Databricks, LLM, and LangChain.
Architected and developed multiple microservices for healthcare data processing, feedback management, and real-time notifications using FastAPI, serving cross-functional teams
Built QuickSight dashboards for log analysis and daily active user tracking
Deployed cloud infrastructure using Terraform across multiple environments
Implemented end-to-end VectorDB deployments with GitLab CI/CD
Developed AWS CDK POC with Clickstream analytics
Built CI/CD pipelines for automated Docker image delivery to ECR
Led TB-scale data migration from legacy healthcare data lake to next-generation platform on Databricks
Architected and developed multiple microservices for healthcare data processing, feedback management, and real-time notifications using FastAPI, serving cross-functional teams, Built QuickSight dashboards for log analysis and daily active user tracking, Deployed cloud infrastructure using Terraform across multiple environments; implemented end-to-end VectorDB deployments with GitLab CI/CD, Developed AWS CDK POC with Clickstream analytics; built CI/CD pipelines for automated Docker image delivery to ECR, Led TB-scale data migration from legacy healthcare data lake to next-generation platform on Databricks
Led PoC for AI-WorkBench data management, deploying MinIO for secure local storage with data sovereignty compliance
Orchestrated Metaflow-based PoC for on-premise data transformation pipeline with modality categorization and thumbnail generation
Pioneered vector embeddings from HL7 non-structured fields within FHIR framework for enhanced healthcare analytics
Implemented scalable VectorDB infrastructure using Terraform
Developed SDK for ingestion, embeddings, and semantic search
Led PoC for AI-WorkBench data management, deploying MinIO for secure local storage with data sovereignty compliance, Orchestrated Metaflow-based PoC for on-premise data transformation pipeline with modality categorization and thumbnail generation, Pioneered vector embeddings from HL7 non-structured fields within FHIR framework for enhanced healthcare analytics, Implemented scalable VectorDB infrastructure using Terraform; developed SDK for ingestion, embeddings, and semantic search
Improved image classification accuracy by 15% using SageMaker
Reduced latency by 50% with CloudFront CDN
Developed chatbot with Amazon Lex and Lambda for appointment scheduling
Utilized Rekognition for facial recognition
Improved image classification accuracy by 15% using SageMaker; reduced latency by 50% with CloudFront CDN, Developed chatbot with Amazon Lex and Lambda for appointment scheduling; utilized Rekognition for facial recognition
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