Product Manager – LLM-powered Conversational Product

Job Description

Product Manager | Hinge Health

The Tone:
This is a full-time, hybrid role at Hinge Health, located in San Francisco, CA. Hinge Health builds an AI-powered human-centered care model focused on musculoskeletal (MSK) conditions, serving over 20 million people across more than 2,550 employers. This role is critical in leading the end-to-end experience of an LLM-powered member-facing hybrid care assistant, directly shaping member experience, driving engagement and retention, and reducing care team workload. Your work will advance the company’s strategy for intelligent, scalable care delivery.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: Hybrid, San Francisco, CA
• Pay: $134000–$201600 yearly
• Team: Intelligent Care team
• Mission: Lead the end-to-end experience of our member-facing hybrid care assistant, an LLM-powered conversational product that helps bring high-quality MSK care to wherever our members are.

What You’ll Actually Do
• Evaluate: Establish clear baselines and evaluation frameworks for engagement, conversational success rates, and care team workload reduction.
• Develop: Ship meaningful improvements to the care assistant, including new use cases, enhanced conversation flows, or safety/guardrail updates, that measurably impact key KPIs.
• Engage: Drive a measurable increase in member engagement by expanding the assistant’s ability to deliver timely, personalized, and high-quality guidance.
• Automate: Achieve reductions in Care Team workload by increasing the percentage of member needs handled safely and effectively through hybrid automation.
• Iterate: Improve conversational performance through continuous iteration on prompts, workflows, escalation logic, and quality metrics.

The Must-Haves
• Background: 2+ years of experience as a Product Manager building and shipping AI-driven software products.
• Experience: Direct experience working with LLM-powered products, including model-driven features, conversational interfaces, or agent-like systems, and driving cross-functional initiatives with Engineering, Design, Data Science, and specialized partners.
• Skills: Familiarity with prompt design, evaluation frameworks, and LLM performance measurement, coupled with strong analytical skills to use data for problem definition, tradeoff evaluation, and decision-making.
• Bonus: Experience with AI safety, guardrails, or human-in-the-loop systems, a background in healthcare, digital health, or regulated environments, prior work collaborating with clinical teams or subject-matter experts, or experience building member-facing products at scale, particularly those driving engagement, retention, or behavior change.