Lead research initiatives advancing enterprise agentic AI, including agent memory, continual learning, resilience, safety, threat detection, privacy, and responsible AI. Define research agendas, publish influential work, validate hypotheses against deployed systems, and provide scientific leadership across researchers, engineers, product teams, and executives. Develop production-quality research software and influence technical decisions across the organization.

Own and develop agent execution harness infrastructure for enterprise AI, including orchestration, reliability, observability, prompt management, evaluation frameworks, LLM integration, and multi-agent system boundaries. The role requires shipping production generative AI features, optimizing model cost and latency, designing distributed systems and APIs, and providing technical leadership through architecture, code reviews, and mentoring.