Lyndon Shi is a senior software engineer with 11 years of experience focused on distributed systems, optimization, and turning research prototypes into production services. Currently at Snowflake and previously at Microsoft, he was the first engineer on a team that productionized the Confidential Consortium Framework for Azure Confidential Computing, contributing across orchestration, SDKs, and tooling. He enjoys leading greenfield projects and investigative engineering, with hands-on contributions to prominent open-source projects like the CCF repo and the azurerm Terraform provider. With a background in optimization research from the University of Michigan, he has applied mathematical methods to generate privacy-preserving test cases and stressed solver behavior with realistic congested network scenarios. Based in the Greater Seattle area, Lyndon pairs deep systems design with mentorship and a knack for shipping secure, production-ready distributed services.
10 years of coding experience
5 years of employment as a software developer
High School Diploma, High School Diploma at Middlesex County Academy for Science, Mathematics & Engineering Technologies
Bachelor of Science in Engineering Computer Science, Bachelor of Science in Engineering Computer Science at University of Michigan College of Engineering
Minor Mathematics, Minor Mathematics at University of Michigan College of Literature, Science, and the Arts
Contributions:9 reviews, 6 commits, 6 PRs in 2 years 5 months
Contributions summary:Lyndon focused on adding configuration file support and transaction rate settings to the CCF framework, specifically enhancing the `cchost` and `perfclient` tools. They also implemented an RPC endpoint to retrieve node IDs based on RPC addresses. Additionally, the user provided an example for generating proposals in Python. The contributions involved modifying core files related to RPC, configurations, and client functionality.
Contributions:6 commits, 3 PRs, 5 comments in 1 month
Contributions summary:Lyndon primarily contributed to the `azurerm_confidential_ledger` resource, adding a new resource to the Terraform provider for Azure Resource Manager. They implemented the necessary code for creating, reading, updating, and deleting the confidential ledger, including handling different ledger types and security principals. Their work involved defining the resource schema, integrating with the Azure API, and creating associated testing infrastructure.
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Lyndon Shi - Senior Software Engineer at Snowflake