Contributed to cloud architecture and helped develop a microservices based serverless application on AWS, leveraging various AWS services like CloudFront, DynamoDB, RDS PostgreSQL, lambda, S3, Step Fn’s, API Gateway, SQS, SNS, SSM etc.

Worked with a team to develop and deploy LLM based GenAI application on Azure Cloud using services like Azure Functions, Blob storage, storage queue, Front door etc.

Conducted load/performance testing using artillery, end to end testing with playwright for LLM/GenAI application.

Led DevOps Initiatives for the application to create CI/CD pipelines using GitHub Actions, Terraform to deploy various microservices.

Architected and created standalone PR environments for different microservices for dev’s to develop/test new features.

Developed new features using ReactJS/Typescript for Front-end & NodeJS/Python for backend of various app components.

Create Test scripts for features using frameworks like Playwright/Cypress/Jest/PyTest to be run as a part of CI/CD.

• Designing, building, testing, and deploying highly scalable, secure, resilient software applications on public cloud services

• Orchestrate serverless workloads on AWS Cloud using services like Lambda, IAM, DynamoDB, API Gateway, S3 etc

• Worked on developing a cloud security posture monitoring/mitigation application leveraging AWS services

• Built and deployed container-based workloads using AWS ECS and docker technologies

• Developed YML based continuous integration/Continuous deployment pipelines in AzureDevOps and Codebuild

• Developed and deployed IAC using tools like Terraform/Terragrunt, AWS Cloudformation

• Building python-based lambda functions for serverless applications using SAM framework.

• Worked closely with Enterprise security team to tighten cloud security by making sure right policies are in place

Developed R,Python and Shell scripts for analyzing datasets greater than 25 gigs.

Utilized supervised/unsupervised machine learning algorithms to perform analysis on cancer cells.

Leveraged cloud/hpc clusters to perform high throughput data analysis.

• Setup Jenkins server, slave nodes, created jobs that automate and facilitate continuous integration and delivery pipelines.

• Setup dashboards and enabled SonarQube scanner for monitoring code quality.

• Administer and set up linux/MacOs systems and write shell scripts to achieve tasks.