Backend Engineer, Global LIVE (AI Infrastructure) - Singapore

About the Team The TikTok LIVE Core Services team is responsible for building the foundational services of the global live streaming platform, covering core data systems such as rooms, users, and leaderboards, supporting real-time interactive experiences for tens of millions of concurrent users. You will tackle real engineering challenges — data consistency, disaster recovery, and large-scale service governance — across a complex global multi-datacenter environment, contributing to a stable, consistent, and efficient live streaming system.

Responsibilities - Participate in the design, development, and continuous optimization of live streaming core services, improving system quality and engineering efficiency - Contribute to stability initiatives for critical live streaming scenarios, including disaster recovery architecture design, monitoring system enhancement, and fault detection and recovery capabilities, ensuring core live streaming experiences under extreme disaster scenarios - Drive service architecture governance, identify systemic risks, and push forward architecture evolution and engineering standards - Participate in the AI-driven evolution of system architecture, designing and developing AI-friendly service architectures and data pipelines

Minimum Qualifications - Bachelor's degree or above in Computer Science or a related field, with a solid foundation in data structures, algorithms, operating systems, and networking - Proficient in at least one backend programming language (Go / Java / C++ / Python, etc.), familiar with microservices and common software architecture patterns - Strong logical thinking and problem decomposition skills, able to independently analyze complex problems and drive resolution - Strong technical curiosity and self-driven learning ability, willing to understand systems at a fundamental level rather than staying at the surface - Good communication, collaboration skills, and a strong sense of engineering ownership

Preferred Qualifications - AI-Native mindset with hands-on experience integrating AI into engineering practices (e.g., AI-powered productivity, intelligent operations) Experience in distributed system design or large-scale service governance