Laurence Rowe is a Principal software engineer with 20 years of experience building reliable, data-driven systems across research and consumer media domains. He has led backend and full-stack work for Stanford’s ENCODE project, architected genomic and biological data platforms at Calico, and improved graph data access and client-server integration at Netflix. A long-time open-source contributor, Laurence has substantive commits to high-profile projects like Plone, React, Falcor and lxml, frequently focusing on robustness, security fixes and performance. He blends deep tooling and infrastructure skills (Postgres, Elasticsearch, AWS, semantic JSON-LD APIs) with pragmatic engineering for production at scale. Based in San Francisco and now consulting, he balances high-leverage systems design with hands-on coding—he also once built video capture/playback software on Raspberry Pi for behavioral labs. He candidly prefers the right fit over hustling for every startup, bringing seasoned judgment as well as technical depth.
20 years of coding experience
16 years of employment as a software developer
Bachelor of Engineering (BEng), Software Engineering, Bachelor of Engineering (BEng), Software Engineering at The University of Manchester
Contributions summary:Laurence primarily contributed to the Plone content management system's core functionality, focusing on bug fixes, enhancements, and security patches. Their work involved modifying setup files to manage versions and dependencies. Additionally, they integrated single sign-on (SSO) features, including modifications to URL handling, login/logout processes, and test cases. Further, they improved the user interface and incorporated fixes related to code injection vulnerabilities.
Contributions:39 commits, 29 PRs, 16 pushes in 2 years 4 months
Contributions summary:Laurence primarily focused on refactoring and improving the core functionalities of the Falcor library. They addressed issues related to data fetching and caching, optimizing the progressive get process to avoid mutating previous result objects. The user also fixed several bugs and addressed linting errors to enhance code quality and maintainability. Additionally, they added and improved several test cases to ensure the reliability of the library.
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