John Mackenzie

Vice President, Software Engineer at Goldman Sachs

New York, New York, United States
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Summary

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Rockstar
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Top School
John Mackenzie is a seasoned software engineering leader with 10 years of experience building and operating large-scale, auditable infrastructure and developer platforms from New York. As a Vice President and former Senior SRE, he has led cross-functional teams to design observability and CI/CD solutions, migrate monolithic tooling to GitLab, and standardize Python architectures across global projects. He excels at infra-as-code at scale—managing tens of thousands of Terraform lines across multi-cloud environments—and has built tooling (including REPL-driven Clojure wrappers and GraalVM CLIs) to make infrastructure safe and testable. His work spans configuration management, VM automation with NixOS, and secure application exposure via authenticated reverse proxies, always emphasizing reproducibility and compliance (SOC2 evidence tooling). Known for mentoring engineers and collaborating with ops and network teams, he translates operational constraints into maintainable software patterns. Counterintuitively for a VP, he still writes and ships low-level automation and developer-facing CLI tools that become team standards.
code10 years of coding experience
job5 years of employment as a software developer
bookBachelor's degree, Computer Science, Bachelor's degree, Computer Science at Purdue University
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Github Skills (38)

machine-learning-models10
data-science10
machine-learning10
inference10
reinforcement-learning10
sagemaker10
amazon-sagemaker10
huggingface10
deep-learning10
mlops10
aws10
jupyter-notebook10
pytorch9
python9
microsoft-azure9

Programming languages (5)

C#JavaJupyter NotebookMarkdownPython

Github contributions (5)

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easyj2j/sagemaker-python-sdk

Feb 2021 - May 2024

A library for training and deploying machine learning models on Amazon SageMaker
Contributions:10 pushes, 5 branches in 3 years 3 months
amazon-sagemakermachine-learning-models
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
Contributions:2 pushes in 8 months
sagemakeramazon-sagemakerdeep-learningreinforcement-learningamazon
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