Tech Lead Software Engineer, AI & Agent - TikTok Ecosystem & Platform

Description

About the Team
The TikTok PGC-Ecosystem & Platform team is a global team responsible for ensuring the health and sustainable growth of the content ecosystem. We take on the responsibility of building next-generation backend systems powered by AI and Agents, collaborating with product managers, data scientists, and strategy operations teams. Together, we develop intelligent content understanding, risk identification systems, and automated governance platforms—utilizing cutting-edge technologies like LLMs and RAG—to ensure high-quality content distribution and a fair, creative environment for users and creators worldwide.

As a core Tech Lead Software Engineer, you will go beyond routine coding to design and implement intelligent, scalable solutions. You will work at the intersection of business logic and cutting-edge technology to drive ecosystem efficiency.

Responsibilities:
- AI & Agent Integration: Collaborate with product managers and data scientists to design and implement backend architectures that integrate LLMs and Agent-driven workflows into real-world business scenarios.
- System Architecture & Optimization: Design and maintain high-performance backend services, ensuring system reliability, scalability, and extensibility to support complex ecosystem governance logic.
- End-to-End Solution Delivery: Deeply understand TikTok’s product ecosystem to develop and deploy end-to-end technical solutions that address content quality and platform integrity.
- Technical Excellence & Growth: Drive engineering best practices within the team, solving complex technical challenges while growing alongside a team of high-caliber engineers.
- Cross-Functional Collaboration: Actively contribute your technical expertise and perspectives to the product development lifecycle, helping the team iterate and scale effectively.

Requirements

Minimum Qualifications
- BA/BS Degree in Computer Science or related major; Strong knowledge of data structures and algorithms, proficient in at least one coding language, including but not limited to Go, Java, Python, C++, Javascript, TypeScript;
- Curiosity towards new technology and outstanding ability to analyze and solve problems;
- Good grasp of software engineering and how to build a system in scalable and extensive manner.

Preferred Qualifications
- Hands-on experience in LLM and Agent application engineering: Proven experience in shipping real-world LLM applications, such as RAG-based intelligent assistants, Agent-driven business workflow orchestration, or LLM-powered content understanding and decisioning systems.
- Experience with workflow or policy/rule engines: Led or played a core role in the design and development of workflow engines, rule engines, or policy/strategy engines, with a solid understanding of their underlying principles.
- Experience in architecting complex business systems: Experience building complex business systems from the ground up, with deep understanding and hands-on practice in Domain-Driven Design (DDD) and/or Event-Driven Architecture (EDA).
- Background in big data and algorithms: Familiar with data analysis, machine learning, or recommendation system technologies. Experience in domains such as content ecosystem, risk control, search, or related areas is highly preferred.