Teagan Glenn
Lead Solutions Architect at Aetna, a CVS Health Company
Aurora, Colorado, United States
Summary
🤩
Rockstar🎓
Top SchoolTeagan Glenn is a Lead Solutions Architect with two decades of engineering experience and a track record of turning complex automation challenges into reliable, production-ready systems. Based in Aurora, Colorado, he bridges hands-on development, MLOps, and architecture—contributing to notable open-source projects like Seldon Core where he improved REST API binary/text handling for scalable ML deployments. He has led cross-functional teams to modernize GraphQL platforms, migrate large systems to Apollo v4/NestJS, and institutionalize self-validating, self-documenting API patterns. Teagan excels at accelerating delivery through end-to-end automation—from device provisioning and network validation at World Wide Technology to CI/CD and mobile platform integrations at Aetna. Known for clear technical communication and conference presentations, he combines deep technical rigor with empathy for product and user needs. An uncommon plus: his career spans embedded systems, cloud-native MLOps, and even practical hands-on ops tooling, giving him a rare full-stack perspective on reliability and scale.
10 years of coding experience
16 years of employment as a software developer
Bachelors Physics, Bachelors Physics at Metropolitan State University of Denver
Github Skills (15)
javas10
api-rest10
rest-api10
api10
apidoc10
api-design10
restful-api10
java10
spring-boot10
kubernetes-pods9
unit-testing9
kubernetes9
mlops8
machine-learning8
bytestring8
Programming languages (12)
Github contributions (5)
SeldonIO/seldon-core
Mar 2020 - Apr 2020
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Role in this project:
Back-end Developer & MLOps Engineer
Back-end Developer & MLOps EngineerContributions:8 commits, 1 PR, 9 comments in 3 days
Contributions summary:Teagan's contributions primarily focused on enhancing the REST API of the Seldon Core engine. They implemented features to process text and binary payloads, including adding converters for octet streams. The user also added unit tests and refined the code by utilizing ByteString for handling binary data. Additionally, the user’s commits updated the application to accept byte arrays and updated the test configuration, showcasing a focus on API functionality and data handling.
monitorservingdata-sciencedeploymentmachine-learning
constructorfleet/HomeAssistant-Config-Tracker
Sep 2019 - Oct 2020
Contributions:173 pushes, 1 branch in 1 year 1 month
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