Hippocratic AI
Product Manager For Ai Agents
As a Product Manager for AI Agents at Hippocratic AI, you will shape and optimize the behavior of intelligent healthcare agents built atop cutting-edge language models. You'll work closely with engineering, design, and clinical stakeholders to define agentic workflows, success metrics, and areas for continuous improvement. Responsibilities: Design, spec, and prioritize AI agent functionalities tailored to healthcare workflows. Collaborate with engineers on prompt engineering, tool calling, and real-time LLM behavior. Monitor deployed agents for quality, safety, and performance issues. Define success criteria and evaluation strategies for agentic features. Drive iterative improvements based on user feedback and internal benchmarks. Qualifications: 4+ years in product management with at least 2+ years in LLM-focused or agentic AI applications. Deep understanding of LLM engineering concepts including prompt engineering, RAG, tool usage, and real-time decisioning. Proven ability to define product requirements and success metrics in ambiguous environments. Experience launching ML/AI-powered products in production.
As a Product Manager for AI Agents at Hippocratic AI, you will shape and optimize the behavior of intelligent healthcare agents built atop cutting-edge language models. You'll work closely with engineering, design, and clinical stakeholders to define agentic workflows, success metrics, and areas for continuous improvement. Responsibilities: Design, spec, and prioritize AI agent functionalities tailored to healthcare workflows. Collaborate with engineers on prompt engineering, tool calling, and real-time LLM behavior. Monitor deployed agents for quality, safety, and performance issues. Define success criteria and evaluation strategies for agentic features. Drive iterative improvements based on user feedback and internal benchmarks. Qualifications: 4+ years in product management with at least 2+ years in LLM-focused or agentic AI applications. Deep understanding of LLM engineering concepts including prompt engineering, RAG, tool usage, and real-time decisioning. Proven ability to define product requirements and success metrics in ambiguous environments. Experience launching ML/AI-powered products in production.