Job Description

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

Design orchestration layers for coordinating vertical domain agents

Build modular Skill systems for extensibility and reuse

Define execution graph standards and planning abstractions

Establish traceability mechanisms for debugging and auditability

- Develop Open Risk Detection Capabilities

Architect systems capable of identifying previously unseen risk patterns

Implement execution trace–driven optimization loops

Translate feedback signals (FP/FN, reviewer overrides, drift signals) into system improvements

Enable proactive rather than purely reactive detection systems

- Establish Engineering Standards for Agent Systems

Define traceability, observability, and guardrail requirements

Evaluate and integrate multi-agent frameworks where appropriate

Ensure production-readiness, scalability, and reliability

- Provide Technical Leadership

Own the technical roadmap for Agent and multi-agent systems

Partner cross-functionally with Risk, Safety, Infra, and ML teams

Mentor engineers and drive architectural rigor