AI Agent Engineer

Responsibilities

Team Introduction We are the core team responsible for the performance experience of TikTok LIVE, dedicated to safeguarding and continuously enhancing the end-to-end experience for billions of users worldwide—from discovering a live stream to the moment creators go live. In the context of globalization, with diverse network environments, device ecosystems, and user behaviors, we proactively identify performance bottlenecks and experience gaps by building a systematic end-to-end metrics framework and diagnostic system. We champion “AI-driven” and “proactive leadership” as our core value creation principles. Our mission is to build industry-leading performance analysis agents and intelligent platforms—automating repetitive analysis into scalable insights, and leveraging technological innovation to directly improve live streaming experience and drive business growth at a global scale. Here, you will have the opportunity to: - Work at the forefront of technology: Help build industry-leading performance analysis agents and redefine the paradigm of performance optimization in the live streaming domain. - Create real business impact: Your work will be applied to one of the world’s largest live streaming platforms, solving complex, high-impact technical challenges. - Unlock significant growth opportunities: Grow in a fast-moving, innovation-driven global team, and collaborate with top talent worldwide. We believe the best talent is driven to solve the most important problems using cutting-edge technologies. If you are passionate about AI, performance optimization, and delivering exceptional user experiences, we look forward to building a smoother and smarter LIVE future with you. Core Responsibilities As a core member of the team, you will be deeply involved in the design, R&D, and platform implementation of the Performance Analysis Agent, transforming cutting-edge AI technologies into a powerful engine that drives business growth. 1. Design and develop the core capabilities of the Performance Analysis Agent Lead or contribute to developing AI-powered capabilities for the performance analysis workflow, including but not limited to: - Automatic Data Inspection and Attribution: Real-time monitoring, anomaly detection, and minute-level automated attribution of massive performance metrics. - Automation of Experimental Analysis: Automatically generate scientific and rigorous A/B experiment reports to improve decision-making efficiency and quality. - Thematic Analysis Assistance: Provide AI support for complex performance topics (e.g., power consumption, smoothness, loading speed) and produce in-depth insights at scale. - Shift-Left Code Performance Review: Integrate AI into the Code Review (CR) phase to automatically detect performance risks, identify issues early, and address them at the source. 2. Build and evolve the Agent platform and services Contribute to the development and evolution of the team’s Agent platform, upgrading traditional APIs to a more powerful and flexible MCP (Model-Controller-Proxy) service framework. Strengthen the data and tooling foundation to enhance overall scalability, reusability, and reliability. 3. Continuously improve Agent core performance Leverage industry-leading technologies to enhance the Agent’s accuracy and efficiency in understanding, retrieval, decision-making, and response, including: - Prompt Engineering and Chain of Thought (CoT): Design and optimize prompts to fully unleash large model capabilities. - Retrieval-Augmented Generation (RAG): Combine with high-quality knowledge bases to improve accuracy and timeliness of responses. - Function Calling: Extend the Agent’s ability to interact with external tools and data sources. - Memory Mechanism and Evaluation Iteration: Enable the Agent to learn and iterate while establishing a robust, scientific evaluation system. 4. Drive the AI value closed loop Deeply understand live streaming business and technical pain points, identify opportunities for AI-driven innovation, and work closely with business, product, and R&D teams to turn AI solutions into measurable outcomes—improving R&D efficiency, service quality, and user experience metrics.

Qualifications

Minimum Qualifications: We value your passion for technology, understanding and insight into business, as well as past achievements. We hope you possess excellent fundamental capabilities and growth potential: 1. Strong engineering and implementation skills Possess excellent coding ability and solid software engineering fundamentals. Familiar with at least one mainstream backend development language (e.g., Go, Python, Java, Rust, C++), and capable of independently designing and implementing complex systems. 2. Familiarity with the LLM and Agent technology ecosystem Have a deep understanding of large language models (LLMs), be familiar with mainstream Agent paradigms, and have practical experience integrating AI technologies into real-world workflows (partial experience is also acceptable). 3. Excellent problem decomposition and system design skills Able to clearly break down and abstract complex, ambiguous business problems into scalable system architectures and reusable technical solutions. 4. Strong technical curiosity and learning ability Maintain a high level of enthusiasm for cutting-edge technologies, continuously follow industry best practices, and quickly learn and apply new knowledge to practical work. Preferred Qualifications: - Hands-on project experience with AI Agents or related fields, including leading or deeply participating in Agent design and implementation. - In-depth understanding or work experience in performance analysis, observability, or data analysis. - Basic knowledge of the live streaming technology stack (e.g., audio/video, network transmission, rendering). - Active participation in high-quality open-source projects or recognized influence in the technical community.

Job Information