Suzie Jang
Director Of Cloud FinOps at (주)우아한형제들 (Woowa Bros.)
Seoul, South Korea
Summary
👤
Senior🎓
Top SchoolSuzie Jang is a seasoned cloud and IT finance leader with 11 years of experience driving cost efficiency and large-scale program delivery across enterprises in Seoul. As Director of Cloud FinOps at Woowa Bros., she builds and leads teams to optimize cloud spend and operational practices, drawing on prior roles at AWS and major IT and consulting firms. Her background combines hands-on technical contributions—such as improvements to the tensorflow/rust bindings for better Windows build support—with program management of global SAP rollouts and multimillion-dollar IT outsourcing contracts. Suzie’s blend of cloud cost engineering, vendor management, and ITIL-based service optimization enables measurable savings while keeping complex systems reliable. She holds a master’s in Information Technology from QUT and is known for bridging deep technical detail with pragmatic financial governance.
11 years of coding experience
12 years of employment as a software developer
Master’s Degree, Information Technology, Master’s Degree, Information Technology at QUT (Queensland University of Technology)Bachelor’s Degree, Educational/Instructional Technology, Bachelor’s Degree, Educational/Instructional Technology at Ewha Womans University 이화여자대학교
English, Korean
Github Skills (7)
machine-learning10
build-system10
rust10
tensorflow10
windows9
api-design8
git6
Programming languages (12)
Github contributions (5)
tensorflow/rust
Nov 2017 - Apr 2018
Rust language bindings for TensorFlow
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 commits, 3 PRs, 5 comments in 4 months
Contributions summary:Suzie primarily contributed to the `tensorflow/rust` repository by making improvements to the build process and core functionality. This included specific adjustments for Windows compatibility, such as modifying build scripts to correctly link TensorFlow libraries. Additionally, the user addressed code readability and corrected minor issues related to scalar tensor handling. The contributions also encompassed refactoring the example directory structure to improve consistency.
rustmachine-learningtensorflowrust-languagerust-lang
bekker/hanji-mediawiki
Nov 2015 - Apr 2021
Contributions:2 releases, 43 commits, 41 pushes in 5 years 5 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.