Litao Hao
Software Development Manager at Amazon
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolLitao Hao is a pragmatic software development manager in Seattle with 16+ years of hands-on engineering and 6 years in formal leadership roles, currently leading LLM-powered shopping and search experiences at Amazon. He combines full‑stack expertise—backend systems, relational databases, and frontend rendering—with cloud-native architectures on AWS to deliver scalable, experiment-driven products that reduced operational load and drove multi‑billion dollar business impact. A strong builder of teams and platforms, he has scaled organizations from zero to high-performing groups, established engineering standards, and automated self‑service systems that saved dozens of SDE‑months annually. An active open-source committer in core distributed systems projects (Apache Hadoop, HBase, Pulsar, StarRocks and CNCF CubeFS), he brings deep distributed storage and observability experience—often improving metrics, logging, and cluster resilience—that informs his production systems design. Notably, he blends low-level systems contributions with product-facing ML and ranking work, making him comfortable across the stack from electing partition leaders to launching customer-facing features.
6 years of coding experience
13 years of employment as a software developer
high school, high school at NO.2 Middle School of Shijiazhuang/No.2 High School ShijiazhuangMaster, Computer, Master, Computer at Tsinghua University
English
Github Skills (37)
monitoring10
hbase10
develop10
messaging10
back-end-development10
configuration-management10
storage10
databases10
hdfs10
distributed-systems10
pulsar10
hadoop10
queuing10
java10
data-storage10
Programming languages (5)
Github contributions (5)
apache/hadoop
Feb 2021 - Nov 2022
Apache Hadoop
Role in this project:
Back-end Developer
Back-end DeveloperContributions:453 reviews, 184 commits, 165 PRs in 1 year 9 months
Contributions summary:Litao contributed to the Apache Hadoop project, specifically enhancing the HDFS (Hadoop Distributed File System) component. Their work involved making parameters configurable for DataNodeDiskMetrics, SlowDiskTracker, and SlowPeerTracker, which are critical for the health and performance monitoring of the distributed storage system. Additionally, they removed unused configurations and parameters, and added features such as adding the namenode address to logs and fixing JavaDoc documentation.
apachebig-datasparkhadoopjava
cubefs/cubefs
Sep 2022 - Dec 2022
cloud-native distributed storage
Role in this project:Back-end Developer
Back-end DeveloperContributions:7 reviews, 18 commits, 21 PRs in 3 months
Contributions summary:Litao's contributions primarily revolve around enhancing the `cubefs/cubefs` cloud-native distributed storage system. They focused on implementing new metrics, like `mpDentryCount` and `badMpCount`, for improved monitoring and visibility into the system's performance. The user also addressed bugs related to cluster management and data partition leader election. Furthermore, they implemented features such as adding the `MaxDpCntLimit` to be set via the CLI and added support for fuse request timeout.
hybrid-cloudstoragecloudnativeopenebsposix
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