Aditya Saligrama

Software Engineer at Formal

San Francisco, California, United States
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Summary

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Senior
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Top School
Aditya Saligrama is a senior software engineer and tech lead based in San Francisco with a decade of experience building secure, large-scale systems and shipping production infrastructure. Currently at Formal he drives least-privilege access for humans and agents via a reverse-proxy approach used by teams at Ramp, Notion, and others, and he hires and interviews for growing security-engineering squads. A Stanford BS/MS in CS focused on systems and security, he has designed and taught the university’s first hands-on cloud infrastructure course and led Applied Cyber teams to national championship-level performances. His background spans fuzzing, adversarial ML, firmware/network security, and high-scale connection testing, and he contributes to open source—improving Snowflake SQL support in the widely used sqlglot parser. Colleagues describe him as equally comfortable prototyping research ideas and turning them into hardened production features.
code10 years of coding experience
job7 years of employment as a software developer
bookHigh School Diploma, High School Diploma at Weston High School
bookMaster of Science - MS Computer Science (Computer and Network Security track), Master of Science - MS Computer Science (Computer and Network Security track) at Stanford University
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Stackoverflow

Stats
13reputation
1kreached
0answers
2questions
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Github Skills (11)

parserator10
parser10
sql-parser10
sql10
python10
snowflake10
transpiler10
nodejs6
stdout6
php6
postfix-notation6

Programming languages (11)

TypeScriptJavaCSSC++CRustJavaScriptGo

Github contributions (5)

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tobymao/sqlglot

Aug 2022 - Aug 2022

Python SQL Parser and Transpiler
Role in this project:
userBack-end Developer
Contributions:20 reviews, 19 commits, 5 PRs in 18 days
Contributions summary:Aditya primarily focused on enhancing the Snowflake dialect within the SQLglot project. Their contributions involved adding support for Snowflake-specific functions such as `TO_TIMESTAMP` and `IFF`, including the necessary parsing and code generation. They also addressed scale handling for timestamp conversions, optimized code related to these new features, and integrated upstream changes to maintain project alignment. Their work directly improved the SQLglot's capabilities in handling Snowflake SQL syntax.
pythontranslationtsqlparserredshift
saligrama/patricia

Nov 2017 - Apr 2018

Contributions:22 commits, 17 pushes, 3 branches in 4 months
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Aditya Saligrama - Software Engineer at Formal