About the role
As a Principal Security Researcher, you will: Lead the design and execution of purple team simulations aimed at making AI safer, conducting realistic AI attacks whose findings inform our security products and help them protect customers more effectively. Develop and execute hands-on attacks against AI systems, including: Direct prompt injection and jailbreaks that bypass system prompts, safety instructions, and alignment. Indirect (cross-domain) prompt injection (XPIA), where malicious instructions are hidden in untrusted content the model consumes: documents, web pages, emails, tickets, code, and RAG sources. Multi-turn, crescendo, and social-engineering style attacks that steer a model toward unsafe behavior over a conversation. Multimodal injection through images, audio, and files that carry hidden instructions. Guardrail, content filter, and safety-system bypass, including encoding, obfuscation, and adversarial phrasing. Sensitive data exfiltration and leakage, including system prompt and grounding-data disclosure and cross-tenant or cross-session leakage. Agentic and tool-use abuse: excessive agency, confused-deputy attacks, unsafe autonomous actions, and manipulation of tools, plugins, and connected systems. Data and model attacks: training-data and RAG poisoning, model extraction, model inversion, membership inference, and adversarial examples / evasion. Build scalable AI red teaming tooling and automation (custom attack harnesses and evaluation frameworks) to generate attack variations, run large evaluations, and continuously test AI systems as they change. Partner with product, engineering, Responsible AI, and detection teams to translate findings into mitigations: better system prompts, input and output filters, grounding controls, agent guardrails, and detections. Evaluate the effectiveness of AI defenses (detections, safety classifiers, filters, and monitoring) and provide strategic recommendations to close gaps. Conduct deep research into emerging AI attacker techniques and map them to frameworks such as MITRE ATLAS and the OWASP Top 10 for LLM Applications. Deliver executive-level briefings, technical reports, and prioritized, actionable recommendations. Act as a technical leader: shape AI simulation methodology, mentor team members, and drive long-term innovation in Security for AI. Doctorate in Statistics, Mathematics, Computer Science, Computer Security, or related field AND 3+ years experience in software development lifecycle, large-scale computing, threat analysis or modeling, cybersecurity, vulnerability research, and/or anomaly detection. OR Master's Degree in Statistics, Mathematics, Computer Science, Computer Security, or related field AND 4+ years experience in software development lifecycle, large-scale computing, threat analysis or modeling, cybersecurity, vulnerability research, and/or anomaly detection. OR Bachelor's Degree in Statistics, Mathematics, Computer Science, Computer Security, or related field AND 6+ years experience in software development lifecycle, large-scale computing, threat analysis or modeling, cybersecurity, vulnerability research, and/or anomaly detection. These
