Kenneth Venegas
Software Development Engineer II - AWS Amazon Q Developer - Agentic AI at Amazon Web Services
Bellevue, Washington, United States
Summary
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Senior🎓
Top SchoolKenneth Venegas is a Software Development Engineer II at AWS with eight years of experience designing serverless, low-latency systems and generative AI developer tooling. He has a track record of turning “unsolvable” problems into practical solutions—improving enterprise browser address bar latency from minutes to seconds at Microsoft and building scalable seller-facing AWS Lambda microfrontends at Amazon. Kenneth specializes in automated code manipulation via syntax parsing, has built migration and analysis tools, and is actively exploring LLM-driven semantic context for agentic AI. He blends front-end UX obsession with strong back-end skills in C#, C++, Java, and TypeScript to deliver delightful, performant products. Notably, he architected a custom NLP/ML search engine that answers questions by parsing Wiki content, showing a bent for moving beyond conventional interfaces. Based in Bellevue, WA, he combines deep engineering craft with a practical focus on measurable customer impact.
8 years of coding experience
12 years of employment as a software developer
Informatica, Computer Science, Informatica, Computer Science at Universidad de Costa Rica UCR
Spanish, English
Github Skills (32)
matching8
to-do8
amazon7
lexer7
abstract-syntax-tree7
pattern-matching7
pattern7
parse7
special-characters7
parser7
amazon-kinesis7
parser-generator6
parsing6
producer6
aws5
Programming languages (3)
Github contributions (5)
kensave/LanguageSyntaxCreator
Nov 2017 - Jul 2019
Language Syntax Parser Based on the LanguageCreator project created by Anton Kropp. I'm having fun trying to parse different programming languages or pieces of them. Parsing programming languages is always a challege, every language has it's own flavor and Syntax. LanguageSyntaxParser takes advantage of how flexible JSON could be and allows you to define all the Language Syntax in a JSON file by specifing the Keywords, Special Characters and Patterns of the language and avoiding you the process of creating an entire AST to parse a piece of code. Since it follows a pattern matching aproach you don't have to define the entire language syntax if you are going to do something simple. So in order to parse just the code you want, it will be required to specifuy only the syntax used by that specific piece of code.
Contributions:21 commits, 1 push, 1 branch in 1 year 7 months
so-simpleastentire-languagepatternsparser
kensave/LanguageSyntaxParser
Nov 2017 - Dec 2017
Contributions:24 pushes in 12 days
elseifdynamic-objectsastexceptionsprogramming-language
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