Design & build the AI layer for autonomous detection, RAG-backed investigation, and auto-remediation workflows. Develop and productionize large-scale LLMs, graph-based reasoning engines, and streaming feature pipelines. Own evaluation & reliability, including prompt libraries, fine tuning, red-team testing, latency budgets, and fallback strategies. Mentor & grow a cohort of AI engineers, run design reviews, uphold code quality, and instill a security-first mindset. Partner with Product, Detection Engineering, and Customer Success to translate attacker behavior into ML and rule-based detections. Experiment with retrieval-augmented generation, tool-calling agents, and multi-modal models.