Tech Lead-Machine Learning Engineer (Agent & Multi-Agent Systems) – AIGC Risk Intelligence
TikTok, Seattle, Washington
About the job
Our team is building the next generation of AI-native risk intelligence systems to address emerging challenges driven by large-scale AIGC content production. As content creation becomes automated and adversaries adopt systematic experimentation (e.g., large-scale template variation and rapid iteration), traditional rule-based and single-model approaches are no longer sufficient. We are transitioning from monolithic LLM applications to a structured multi-agent architecture that emphasizes: Tool-augmented reasoning (ReAct-style systems) Modular skill composition Execution traceability and observability Feedback-driven system evolution Cross-domain risk reasoning We are seeking an experienced technical leader to define and implement this architecture.
Responsibilities
- Architect and Implement Agent Systems
Design structured agent workflows (e.g., Evaluate → Validate → Reflect → Summarize) Implement ReAct-style tool allocation and reasoning frameworks Develop short-term and long-term memory architectures Ensure robustness under adversarial and evolving conditions
- Lead Multi-Agent Architecture Development