Background in AI/ML or security research. Ideal candidates have both, but we're equally open to candidates from data science or security research backgrounds with demonstrated depth in AI systems.

5+ years of experience in the AI or security industry.

Solid understanding of AI agents: how tool use, memory, planning, and orchestration layers interact, and where that architecture introduces risk.

Working knowledge of LLM and agentic security — prompt injection, jailbreaks, tool-use exploitation, memory/context poisoning, and related attack classes.

Knowledge of AI vulnerabilities at both the model and infrastructure layers, and familiarity with effective mitigation strategies (e.g., guardrails, sandboxing, input/output filtering, access controls).

In-depth understanding of LLMs, generative AI, agentic systems, and RAG pipelines — how they're built, where they break, and how failure modes propagate through a system.

Strong research methodology and judgment: experience designing large-scale experiments, forming hypotheses, and applying quantitative rigor to evaluate results, identify signal from noise, and draw defensible conclusions from complex or ambiguous data.

About the role

What you'll do

Requirements

Tech stack