AI Product Manager
Also known as: AI PM, product manager for AI
Traditional product management asks: what should the product do, and does it do that? AI product management adds a harder question: how do you define and measure whether an AI output is good? That requires comfort with evals, an understanding of model trade-offs (latency, cost, accuracy, safety), and an ability to write or review system prompts as a core product artifact.
The role is increasingly showing up as a distinct title in AI startup hiring because the skills are genuinely different from general PM work. A strong AI PM can read an eval suite, understand why a model is failing a class of inputs, write a spec that incorporates failure modes, and communicate model limitations clearly to stakeholders who expect deterministic software behavior.
At smaller AI-native companies, the AI PM role often overlaps with the FDE (founding developer experience) or AI engineer role. At larger companies it's becoming a dedicated function sitting at the intersection of product, data, and ML engineering.