AI Engineering Lead

ABOUT NORMAL COMPUTING Normal Computing builds silicon that turns thermal noise from an obstacle into a computational resource. Conventional chips spend most of their energy forcing determinism onto physics; ours compute with it. Stochastic, in-memory, asynchronous: the result is 10-100× more AI inference per dollar, per watt. We co-design the full stack: AI-native EDA systems in production with the world's largest semiconductor companies, and the advanced ASICs they make possible. Backed by $85M+ from the world's leading deep-tech investors and built by scientists, engineers, and operators from the labs that built modern computing. Normal works as one team across New York, Silicon Valley, London, Copenhagen, and Seoul. We hire people who want the hardest version of their craft, across every discipline, at every seniority. THE ROLE As our AI Engineering Lead, you will lead a team of engineers building systems for AI-native EDA and advanced hardware workflows. This work sits at the intersection of applied AI, ML systems, agents, model evaluation, software engineering, and semiconductor domain complexity. You will be responsible for setting technical direction, managing execution, developing engineers, and staying close to the implementation details that determine whether these systems work in practice. The team is building AI systems where correctness, traceability, and reliability matter, especially when agents are operating against formal or highly structured engineering problems. This is a hands-on leadership role for someone who has grown from strong individual contribution into technical leadership or management. You should be comfortable moving between architecture, model behavior, evaluation, implementation tradeoffs, hiring, and team development. The strongest candidates will have built meaningful AI systems in technical domains where models need to operate against real constraints. WHAT YOU'LL OWN - Team Leadership: Lead and manage a team of AI engineers; hi