Andrew Kutta
Software Engineer at Meta
United States
Summary
👤
Senior🎓
Top SchoolAndrew Kutta is a pragmatic software engineer with 14 years of experience building reliable, cross-language systems and enabling customer-facing teams to better support sellers and users. He blends hands-on full-stack work—Ruby on Rails, Node/TypeScript, React—with a history in Erlang, C#, Java, and embedded systems, and has driven observability and cost-savings initiatives at Square that reduced monthly spend by roughly $200k. Comfortable picking the best tool for the job, he has led platform migrations, designed scalable APIs (including a high-throughput Demand Response API), and built automation like a Support Bot to reduce engineer toil. An active back-end contributor to open-source tooling for repository analytics, he focuses on maintainability and practical features (e.g., whitespace-robust diffs and SSH improvements). He pairs technical delivery with people leadership and measurable system health metrics, and now brings that blend of product-thinking and operability to Meta.
14 years of coding experience
14 years of employment as a software developer
Automotive Technology, Automotive Technology at St. Louis Community CollegeMaster of Science (MS) Computer Science, Master of Science (MS) Computer Science at Washington University in St. LouisBachelors of Science Computer Science, Bachelors of Science Computer Science at Southern Illinois University EdwardsvilleComputer Science, Computer Science at University of Colorado Boulder
English, German
Github Skills (3)
go10
git10
machine-learning5
Programming languages (8)
Github contributions (5)
src-d/hercules
Oct 2018 - Oct 2018
Gaining advanced insights from Git repository history.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:15 commits, 1 PR, 4 comments in 2 days
Contributions summary:Andrew primarily worked on improving the core functionality and maintainability of the project. Their contributions involved adding features to ignore whitespace differences during diff calculations, renaming and refactoring filter-related components and test, and integrating the use of identity files for SSH connections. They also fixed typing and implemented whitespace-related feedback.
git-analysismachine-learningtensorflowmloncodetensorboard-visualizations
akutta/vector
Aug 2022 - Jan 2026
A high-performance observability data pipeline.
Contributions:33 pushes, 9 branches in 3 years 5 months
pipelinedata-observabilityobservabilityperformancedata-pipeline
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