- Built a resilient and self-checking automated billing service for AWS from the group up using Python which brought the budgeting process from being fully manual to fully automated, saving senior members of the team over 20 hours per month.- Remediated and researched over 200 critical and high level security vulnerabilities in the school’s AWS accounts which raised the overall security score in AWS Security Hub from 60% to over 90%.- Led development on Python scripts for billing, maintenance, and inventory which totaled to thousands of dollars saved in the school’s AWS accounts by terminating underutilized or dormant resources.- Constructed containers in AWS Elastic Container Service using Docker, Rancher, and Kubernetes in order to assist other IT departments in transitioning to containerization-based application development.

- Designed and coded a GraphQL/REST based orchestration API from scratch in Node.js using the NestJS framework- Enhanced the RESTful orchestration API to consolidate multiple REST APIs into a unified endpoint and optimized the final response payload- Containerized the RESTful orchestration API within a Docker Container, and deployed to AWS on Fargate as a serverless app.- Created an Oauth based service within the API to create, obtain, and invalidate bearer tokens to be used to call different RESTful APIs.

- Designed highly scalable infrastructure and code used to ingest and process real time data from over 5,000 vehicles every minute with the use of Java, AWS Kinesis Streams, DynamoDB, Lambda, and Apache Flink.- Created a service to track and log delays in real time data, this unveiled over 400,000 instances per month of delayed data and helped the company remediate it.- Built a data pipeline with Java, Python, and Kubeflow to export and visualize over 500,000 geospatial records every month.- Created over 50 Datadog monitors and added authentication tokens to a FastAPI based service to monitor infrastructure health and improve security.- Improved the existing Gitlab CI/CD pipeline by automating the deployment of Terraform code and Docker containers to AWS accounts with Helm and Kaniko which brought the pipeline from being 80% to 100% fully automated.