Tech Lead-Machine Learning Engineer (Agent & Multi-Agent Systems) – AIGC Risk Intelligence
Core
Architecting and implementing next-generation AI-native risk intelligence systems using multi-agent architectures to detect emerging risks in large-scale AIGC content production.
Role type
Senior IC Machine Learning Engineer (Multi-Agent Systems & Risk Intelligence)
Builds
Production-ready multi-agent systems with tool-augmented reasoning, modular skill composition, and execution traceability for risk detection.
Domain
AI Safety / Risk Intelligence / Large Language Models
Deliverable
production ML models
Required skills
LLM-based agent architecture design, ReAct-style reasoning, tool calling systems, workflow orchestration, memory design patterns, distributed AI systems, Python backend engineering, adversarial system operations
Preferred skills
Trust & safety domain expertise, multi-agent orchestration frameworks, execution trace logging, RL-style policy optimization, technical leadership
Technologies
Python, ReAct, Multi-agent frameworks
Responsibilities
Design structured agent workflows and ReAct-style reasoning frameworks; Build modular skill systems and orchestration layers; Architect systems for identifying unseen risk patterns; Define engineering standards for traceability and observability; Mentor engineers and drive architectural rigor.
Seniority
Senior, hands-on IC with leadership responsibilities
