Liang Mei
Engineering Leadership at Temporal Technologies
Seattle, Washington, United States
Summary
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Rockstar🎓
Top SchoolLiang Mei is an engineering leader with 8+ years building and scaling distributed systems, cloud storage, and workflow orchestration, now leading engineering at Temporal Technologies from Seattle. He previously led Uber’s workflow systems team that scaled Cadence to 40+ teams and billions of workflows per month, and helped build a durable timer service handling tens of thousands of timers per second. His background spans storage internals at Dell EMC (ECS) through platform and middleware engineering at Microsoft, giving him deep expertise in persistence, reliability, and high-throughput architectures. An active open-source contributor, he has improved Cadence and Temporal internals—fixing data races, refining error handling, and adding workflow/client features that improve observability and robustness. Known for growing geo-distributed teams and mentoring engineers, he connects low-level systems thinking with product-focused delivery. He combines research-rooted rigor (University of Michigan) with pragmatic production experience, often surfacing non-obvious fixes that prevent large-scale outages.
8 years of coding experience
13 years of employment as a software developer
Master, Electrical Engineering:Systems, Master, Electrical Engineering:Systems at University of MichiganBachelor of Science in Engineering, Computer Science, Bachelor of Science in Engineering, Computer Science at Shanghai Jiao Tong University
Chinese, English
Stackoverflow
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Github Skills (20)
microservice-framework10
testing10
cadence10
distributed-systems10
go-testing10
workflow-automation10
go10
persistence10
functionfs10
logging10
orchestrator-workflow10
orchestration10
engine10
task-management9
workflow-engine9
Programming languages (9)
Github contributions (5)
cadence-workflow/cadence-go-client
Nov 2019 - Feb 2021
Framework for authoring workflows and activities running on top of the Cadence orchestration engine.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 releases, 21 reviews, 21 commits in 1 year 3 months
Contributions summary:Liang focused on enhancing the Cadence Go client, primarily addressing query result size limitations within workflows. Their contributions included implementing a result size limit to avoid performance issues, adding a unit test for the new functionality, and refining error handling related to query execution. They also made changes to expose poller counts as a user option, improving worker configurability. The user also implemented and merged activity registration changes and included workflow await support.
golangworkflow-functionscadenceorchestrationauthoring-workflows
cadence-workflow/cadence
May 2018 - Oct 2020
Cadence is a distributed, scalable, durable, and highly available orchestration engine to execute asynchronous long-running business logic in a scalable and resilient way.
Role in this project:Backend Developer
Backend DeveloperContributions:2 releases, 74 reviews, 33 commits in 2 years 4 months
Contributions summary:Liang primarily focused on improving the Cadence workflow engine's internal workings. Their contributions included adding logging for internal server errors to the clients, improving error handling, and refactoring tests for integration. They also addressed data races and fixed bugs within the codebase, focusing on areas related to persistence and overall system stability. Furthermore, the user made changes to API version checking.
cadenceresilientorchestration-engineservice-buslogic
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