I led a team of 3 engineers to build the new provable exchange. As a tech lead, my responsibility is to facilitate the team to build the best provable exchange with top-notch user experience and developer experience. In addition, I provided detailed code review and guidance for implementing new features on the backend API layer and the frontend dApp. As a contributor, my work includes:

• Exchange user authentication

• API user authentication and authorization

• Two factor authentication

• Fund onboarding and offboarding

• Fund management infrastructure

• User and market websocket infrastructure and subscription management

At Hashflow, we are building a decentralized exchange for cryptocurrencies. As a Senior Engineer, I contributed heavily to following initiatives:

• Rewrite our maker-facing websocket server in Scala/ZIO for performance

• Scope, plan and lead the Solana migration efforts to support Solana tokens on Hashflow

• Improve our test coverage on core request-for-quote flow

I build backend and infrastructure to store and serve nft related data reliably.

SDE II at AWS AI - Computer Vision. Working on textract: https://aws.amazon.com/textract/

• Work with peer and senior engineers to migrate our existing 20+ service pipelines to cdk synthesized pipelines. The migration would enable automatic code deployment, and thus reduce significant time wasted on manual validation and deployment. This initiative was scoped to take 80+ dev weeks due to the complexity of our services, and challenges involved in migrating existing customer to new service.

• Work on moving our document context elastic search cluster from existing service pipeline to cdk synthesized service pipeline.

As a SDE II in Data Tooling Team of Quicksight Q, I worked in a team of 7 which includes SDEs, and MLEs. I contributed significantly in following aspects:

• Lead, design and implement the reviewed answer collection service - a data workflow run internally to collect customer "reviewed" answer to NLQs. These data are collected daily and are used as regression test data to ensure our models are performing consistently in prediction accuracy.

• Lead and design the backend component of data collection portal, a web portal that is built for Business Analysts/Data Scientists to collect, annotate, and validate NLQ data to facilitate science experiments and better our prediction accuracy. The backend service is built in AWS AppSync, GraphQL, typescript lambdas and uses Postgres as data storage

• Research and establish test strategy for data collection workflow, and led the effort to improve test coverage of previously uncovered code significantly. We improved from 50% to 90% coverage, and fixed lots of major bugs.

• Design and implement the automated PostgreSQL migration service in serverless python lambda, which reduced human operations significantly

• Design and implement the python SDK for data collection portal backend, used by our data scientist to interact with collected data

• Work with peer engineers to triage and fix critical issues reported by our customer under tight timeline

• Mentor junior engineers. Provide guidance in daily conversations and code reviews.