| Alexander Saavedra

5 min 12 s

Alexander Saavedra

Email is available upon request only via LinkedIn | San Francisco, CA | LinkedIn | GitHub

Summary

Alexander is a current Staff Solutions engineer working in application security with a strong cybersecurity, machine learning, and software development background. His current role he has been ranked number 1 in his division two consecutive years and won the division West SE of the year award 2022 at Synopsys which is a 21,000+ person company. Alexander has a relentless focus on delivering value to customers with an innovators mindset in all of his work. He focuses on making every day “day one” and making things 10 times better by rethinking what is considered possible. While in College he has worked as a Machine Learning research intern, Machine Learning engineer intern, and engineer intern achieving a UC Major GPA of 3.72 in Machine Learning and Neural Computation. He is currently pursuing a Master’s in Computer Science, Interactive Intelligence (like Machine Learning) at Georgia Institute of Technology which is a top 10 Computer Science program.

Hobbies: Reading, Biking, Weightlifting, Computer Games, Economics and Markets, Writing, Longevity and Health, Pedagogy, exploring future technology trends, poetry

Technical & Analytical Skills

General: Java and Kotlin ecosystem, TypeScript and Javascript, NodeJS, SQL, Postgres, Maven, Gradle, Git, basic Networking, REST APIs and exposure to SOAP, Bash, Linux and general GNU knowledge, LaTeX, Vim, and relational & non-relational databases
Deployment Technologies: Amazon Web Services, Docker, Kubernetes, KiND, GitHub Actions, Azure DevOps, Jenkins, Virtual Machine Infrastructure, Ephemeral Agent Deployment, Firebase
Development Methodologies: Extreme programming, Test Driven Development, Behavior Driven Development, Agile, and Scrum
Application Security Testing: Static Application Security Testing, Software Composition Analysis, Interactive Application Security Testing, Infrastructure as Code, Security in Software Development Lifecycle, and basic Protocol Fuzzing knowledge
Machine Learning: Python 2 & 3, PyTorch, TensorFlow, advanced undergraduate Statistics, Linear Algebra, high dimensional Math, and Multivariable Calculus
Cryptocurrency: Solidity, Remix, Ethereum Virtual Machine, Smart Contract Development, and functional encryption knowledge
Prediction Markets and Forecasting: Ask me, but things like Metaculus.com tutorials and goodjudgment.com may give you some idea what this is. In a fast moving field like software you need to forecast the future with some degree of accuracy, not just precision, to stay relevant

Work Experience

Sr. Staff Solutions Architect | Synopsys Inc | San Francisco Bay Area | 2021 - present

Awarded SE of the Year 2022 for my division West region and promoted to Staff engineer beginning of 2023
Achieved highest division quota attainment of 163% in first year
Highest win rate 68% achieving 2021 for division
Streamlined the product trial navigation process with engineer teams leading to a 200% faster proof of concept cycle
Shadow, mentor, and assist in onboarding 5 senior and 2 staff engineers leading to 150% faster onboarding
Trained engineers on infrastructure as code and modern SDLC best practices resulting in further POC alignment
Spearheaded the initiative for high priority technology integrations like GitHub Actions for SAST and SCA
Received highest possible first year and second year performance review by manager which lead to promotion
Analyze, design, and implement software solutions to meet client requirements.

Solutions Engineer | Launchdarkly | San Francisco Bay Area | 2019 - 2020

Closed 6 figures of product for the fiscal quarter during the pandemic
Worked with the top account executive of the year leading to heavy technical involvement in large enterprise deals
Produced content for marketing, learning department, security, and on site templates

Software Engineer | Bina Technologies acquired by Roche | San Francisco Bay Area | 2016 - 2019

Designed user acceptance tests based on FDA guidelines, implementing Cucumber and Protractor test suites for FDA tests of cancer detection products, achieving over 60% increase in UI test coverage
Created an onboarding program for engineers, which reduced overall ramp time across 10 new hires by 30%
Automated Jenkins jobs using Groovy to run verification suites with smoke tests and long-running feature tests for builds, optimizing 8 hours of manual tests down to 45 minutes of automated tests 10X decrease
Implemented API testing and reporting framework in RestAssured, JUnit, TestNG used by development and QE for testing endpoints, leading to a 36% increase in bug discovery on endpoints
Worked with the lead genomic pipeline engineer and backend engineer to create an analysis pipeline engine database for categorizing cancer types in blood and tissue using relevant and up to date cancer sequence snippets in our sequencing runs
Leveraged SonarQube for guidance in reducing code smells, security vulnerabilities, and code complexity by 92%.

Software Engineer | Redbird Advanced Learning | San Francisco Bay Area | 2014 - 2015

Initiated and executed automated regression testing suites written in Mocha, PhantomJS, BackboneJS, and Ruby Watir increasing bugs discovered in the course curriculum by 200%
Led 3 person team responsible for finding and resolving issues in Math and Language Arts Product, leading to a 50% increase in bugs discovered within the curriculum and resolved

Machine Learning Engineer Intern | Qualcomm Institute | San Diego, CA | 2013 - 2014

Implemented machine learning methods for transforming satellite image data with Python, SciPy, NumPy, and Django Database, leading to path discovered in Valley of the Khans in Mongolia for National Geographic

Machine Learning Research Intern | Redacted Company | San Diego, CA | 2012 - 2013

Project under NDA, I worked as a machine learning researcher for a private company along with help from Professor Virginia de Sa a world renowned Machine Learning, Brain Computer Interface, and Computational Neuroscience researcher

Projects

GarageHub, the Airbnb of garage space

GarageHub: Developed ‘GarageHub’ – AirBnB for garage space – utilizing JavaScript, AngularJS, Firebase, Zapier, and Twilio API, designed to capture a $20Mill+ market of open garage space in San Francisco

Guru Indexer, Guru investor returns for index fund costs

Guru Indexer Guru index which aggregated stock data and metadata from various sources which was I believed would produce a highly concentrated long term outperformance focused strategy for large and small capital US based companies sources included GuruFocus and WhaleWisdom. The rough details are outlined in this blog post https://awsaavedra.com/posts/enterprising-investor.

Strategy was eventually discussed with highly skilled value investors and then discontinued once I learned about a startup that was implementing a strategy that rhymed in their flagship product with more traction and I was able to get their service free with lifetime membership. It pays to be early.

Education

M.S. Computer Science: Interactive Intelligence GPA: 4.0, Georgia Institute of Technology, 2023 - Present

B.S. Machine Learning and Neural Computation UC MGPA: 3.72, Minor in Computer Science, University of California San Diego

CoFounder and Principal Member, Hackathons at UC San Diego 2013 - 2014