Full Stack Developer
Experience
2024 — Now
2024 — Now
New York, New York, United States
Paze Product Engineering Team
2023 — 2023
2023 — 2023
• Led the design and development of user interface for a live cloud health assessment application for Capital Group
• Developed CRUD interfaces using CSS, Javascript, and React utilizing several DynamoDB databases and features for both admins and users
• Implemented pagination, asynchronous search, sorting, and notifications for cloud dashboards, features, and tables
• Utilized Pytest for integration tests of Lambda functions to validate build before deployment in CodePipeline
• Integrated multi-factor authentication with Cognito-based backend using Lamda and SES
• Developed RESTful APIs using API Gateway and Lambda in Javascript and Python for several cloud applications
• Implemented Terraform code to generate AWS-based backend consisting of Cognito, S3, Lambda, API Gateway, DynamoDB, and SES
• Contributed to TypeScript-based npm package allowing developers to import sign up / login API modules and interfaces to expedite user authentication development
2022 — 2022
2022 — 2022
• Developing AWS Lambda functions and endpoints in C# backend for cloud-based electronic notarization web application for First American Docutech
• Utilizing Moq framework for development of unit tests to validate new APIs before deployment
• Deploying API Gateway and Lambda backend to cloud using Terraform for testing with CloudWatch / Postman
• Collaborating on software development using Scrum model of agile project and team management with Jira
2021 — 2022
Los Angeles, California, United States
• Co-developed and characterized an existing structured photonics low-energy prototype system
• Operated femtosecond laser OneFive Origami-15 for the generation of light by design
• Researched the development of programmable, unprecedented spatio-temporal precision, structured photonics
2021 — 2021
Los Angeles, California, United States
• Implemented automated image segmentation of x-ray magnetic images using TensorFlow-based convolutional neural network U-Net
• Co-developed a generative adversarial network (GAN) for the resolution enhancement of x-ray magnetic images
• Researched the properties and theory behind multiferroics at the nanoscale level
Education
UCLA