are accepted until further notice.
Your Impact
As a Lead Researcher, you will play a pivotal role in investigating, analyzing and mitigating emerging threats targeting AI / ML. You will work closely with the Director of AI Threat Intelligence to build a world-class AI threat research capability, delivering actionable intelligence, advancing the state of AI security research, and helping secure Cisco’s AI-driven products and services. You will collaborate with fellow researchers, data scientists, security engineers, and product teams to proactively identify AI-related risks, with a strong focus on securing autonomous AI agents.
Key Responsibilities
- Lead research into AI/ML-specific threats, including adversarial attacks, prompt injection, model exploitation, data poisoning, model evasion, tool misuse and misuse of generative AI systems.
- Conduct threat modeling of AI agents and multi-agent systems, including Model Context Protocols (MCP), A2A — ensuring safe transmission and handling of context, memory, and system metadata across model calls and between AI Agents.
- Track evolving threat actor tactics, techniques, and procedures (TTPs) targeting AI/ML ecosystems, particularly those exploiting agentic behavior and context management flaws.
- Produce and publish high-quality, actionable threat intelligence reports, technical analysis papers, and internal briefings to inform engineering, product, and executive teams.
- Represent Cisco in external research communities, conferences, working groups, and standards organizations where AI security and threat intelligence are advancing.
- Mentor junior researchers and contribute to building a center of excellence around AI threat intelligence and adversarial research.
Qualifications
- 8+ years of experience in cybersecurity threat intelligence, adversarial research, red teaming, or offensive security, with exposure to AI/ML systems preferred.
- Strong expertise in AI/ML technologies, particularly generative models, AI agent frameworks, memory-augmented AI, and Model Context Protocol (MCP) designs.
- Hands-on experience analyzing vulnerabilities in AI systems, including prompt injections, agentic exploits, and context/memory transmission flaws.
- Proficiency in Python or similar scripting languages for prototyping, simulation, and analysis.
- Familiarity with threat frameworks such as MITRE ATLAS, ATT&CK for AI, or emerging AI-specific threat models.
Preferred Qualifications
- Record of contributions to AI security research communities (publications, CVEs, conference presentations, open-source projects, blogs).
- Knowledge of responsible AI practices, secure, safe deployment of autonomous and agentic AI systems.
- Familiarity with securing agent-to-agent communication protocols, and external tool orchestration in multi-agent environments.
- Experience working with AI/ML pipelines in cloud environments (AWS, Azure, GCP).