Yongsheng Xie

Software Development Engineer

As an experienced Software Development Engineer, I made significant contributions to Tencent WeChat’s Channel, designing core systems and optimizing a high-capacity message delivery system for over 100 million users. Known for enhancing functionalities and reliability, my work at WeChat and AWS reflects innovative solutions, a profound impact on user experience, and expertise in managing large-scale, high-traffic platforms.

Work Experience

Software Development Engineer II

Amazon Web Services | Apr 2023 - Nov 2023

Led the development of an efficient data pipeline for aggregating AWS user usage data and created a robust service to streamline and secure data deployment processes for product managers at AWS.

  • Led the design and implementation of a data pipeline for aggregating AWS user usage data, skillfully utilizing AWS Athena and AWS Lambda to ensure efficient and accurate data processing.
  • Developed and launched a service aimed at enhancing data deployment processes for product managers, focusing on safety and robustness. This initiative significantly improved the reliability and efficiency of deploying hand-prepared data within the AWS ecosystem.

Backend Software Engineer

Tencent | Jan 2020 - Mar 2023

Crucially contributed to the early-stage development and scaling of WeChat Channel, designing key systems and optimizing a live stream message delivery system to support 100 million daily users and over 2 billion daily messages.

  • Designed and implemented core social interaction systems, including comments, likes, favorites, and notifications, alongside contributing to the development of the account system. This work was integral to user engagement and platform interactivity.
  • Played a pivotal role in the development of the WeChat Channel live streaming platform, assisting in creating the live chat system, implementing promotional item delivery mechanisms (e.g., advertisements), and integrating e-commerce features.
  • Architected and optimized a high-capacity live stream message delivery system, capable of handling over 2 billion messages daily for an audience exceeding 100 million, while maintaining average cluster resource utilization below 50% during peak hours.

DevOps Engineer

Tencent | Aug 2018 - Jan 2020

Enhanced and maintained key internal operational platforms, and notably designed a three-tiered job execution platform that boosted operational efficiency by 60% and reduced downtime.

  • Actively participated in the maintenance and development of several key internal operational platforms, including a DNS records management system, configuration center, and system alarm message delivery system, ensuring their reliability and efficiency.
  • Designed and implemented a sophisticated three-tiered system architecture for a batch script and command job execution platform, specifically tailored for Ops Engineers. This new system not only increased the execution speed of operational jobs by 60% compared to the previous system but also facilitated seamless switching between different operational instruction execution platforms with minimal downtime.

Highlighted Projects

WeChat Channel Live Stream Messaging System

WeChat, Tencent

Developed and optimized a scalable message delivery system using long-polling technology, enhancing real-time communication and resource efficiency across variable user loads.

  • Developed a robust message delivery system utilizing long-polling technology, ensuring efficient and real-time communication.
  • Implemented an innovative automatic adjustment mechanism for long-polling hold times, significantly enhancing system resource utilization by 30 percent.
  • Strategically optimized resource usage for the live chat message delivery process by intelligently dispatching requests across specialized clusters.
  • Designed a dynamic service clustering system based on real-time analytics, capable of scaling to accommodate varying sizes of live sessions determined by peak concurrent user metrics. This approach employed three distinct cluster sizes (small, intermediate, and large) to efficiently manage resources for different user group sizes.

WeChat Channel Hashtag (Topic) System

WeChat, Tencent

Designed and enhanced a scalable topic management system for WeChat, integrating advanced features and leveraging message queues for consistent data operations.

  • Engineered a highly extensible system for efficient management and storage of topic data, ensuring scalability and adaptability to evolving requirements.
  • Expanded the system’s capabilities by integrating advanced features such as Event tracking and POI (Points of Interest) hashtags, enhancing user engagement and data richness.
  • Leveraged message queues to maintain eventual consistency in topic data operations, adeptly navigating the constraints of our internal spanner-like database lacking multi-table transaction support. This strategy ensured robust data integrity and system reliability in a complex database environment.

WeChat Channel Comment System

WeChat, Tencent

Optimized comment data handling in WeChat Channel's comment system, enhancing read performance by 60% and implementing a fan-out writing strategy to meet product specifications for varied comment ordering.

  • Conducted in-depth analysis of comment data reading patterns and implemented strategic optimizations including indexing, effective caching mechanisms, and periodic pre-calculated views of database data, resulting in a 60% improvement in read performance.
  • Analyzed comment data writing patterns and employed a fan-out writing strategy to provide fast-loading, tailored comment displays, in compliance with product specifications for varying comment order presentations.


WeChat, Tencent

Significantly enhanced WeJobs by developing a flexible job execution platform integration layer, deploying a high-performance message queue for efficient scheduling, achieving a 60% improvement in system performance, and implementing both a robust self-healing mechanism and a multi-version compatible user access layer.

  • Developed a versatile abstraction layer to seamlessly integrate various operational job execution platforms, enhancing system flexibility and adaptability.
  • Achieved a significant 60% improvement in system performance compared to the previous setup, through comprehensive optimizations and refinements across the platform.
  • Engineered a robust job self-healing mechanism, ensuring complete recovery and continuity of all jobs after system crashes or restarts, thereby significantly improving system reliability.
  • Implemented a user access layer compatible with multiple API protocol versions, streamlining system migrations and ensuring seamless user experiences during transitions.