Glenn Fisher is a multidisciplinary software engineer with a BSE in Electrical Engineering from Princeton and a decade of experience building cloud, mobile, and embedded systems. He has led engineering efforts at IBM and State Street—shipping language SDK generators for Watson services and scaling a private OpenStack cloud while reducing development costs by 90%. At Slingshot Aerospace he applied signal-processing AI to satellite and drone data, blending systems, ML, and embedded expertise to improve situational awareness. A hands-on contributor to notable open-source Watson SDKs in both Node.js and Python, he bridges code generation, test automation, and full-stack delivery. Known for turning cross-disciplinary ideas into practical products, he often finds novel intersections between hardware and software to solve tough real-world problems.
10 years of coding experience
6 years of employment as a software developer
Bridgewater-Raritan Regional High School
BSE, Electrical Engineering, BSE, Electrical Engineering at Princeton University
:snake: Client library to use the IBM Watson services in Python and available in pip as watson-developer-cloud
Role in this project:
Full-stack Developer
Contributions:42 commits, 9 PRs, 8 pushes in 1 month
Contributions summary:Glenn's primary contribution involved refactoring and updating the conversation_v1.py file, which is the client library for the IBM Watson Conversation service. This included generating code using WatsonPythonCodegen and subsequently fixing manual naming conflicts to resolve generation errors. The user also formatted the generated code using YAPF and replaced the test file with generated stubs. Finally, the user updated several files to reflect recent releases.
:comet: Node.js library to access IBM Watson services.
Role in this project:
Back-end Developer
Contributions:24 commits, 21 PRs, 6 pushes in 22 days
Contributions summary:Glenn contributed to the development of the Tone Analyzer service by generating code for the service. They implemented a new feature by generating the tone analyzer service. They also worked on the test files for the tone analyzer including adapter and integration tests. Additionally, the user updated the test to match the generated API.
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