Defines Rapid7’s technical vision and architecture for LLM and agentic AI systems across security products. Leads model strategy, fine-tuning, post-training, inference optimization, evaluation standards, and high-risk initiatives. Builds critical training and inference code, resolves complex technical trade-offs, mentors senior engineers, and influences product and platform strategy. The role requires deep expertise in transformer-based models, PyTorch, distributed training, context engineering, model evaluation, scalable inference, classical ML, and production AI systems.

Lead the technical direction for LLM and agentic AI systems across Rapid7’s security products. Architect, fine-tune, evaluate, optimize, and deploy models at scale while establishing engineering standards for context engineering, inference, and release evaluations. The role remains hands-on with model and infrastructure code, leads complex design decisions, mentors senior engineers, and shapes cross-functional product and platform investments.