Product Manager, Agent Intelligence

Sage Care Inc • Palo Alto, CA

3d • $150,000 - $185,000

About The Position

Sage Care is a fast-growing, early-stage healthcare startup transforming care navigation with AI. Our platform helps patients find the right care, enables providers to focus on the people who need them most, and improves access, quality, and economic outcomes at scale. Founded by leaders from Apple, Uber, and Carbon Health, Sage Care is backed by top-tier investors including General Catalyst and Chelsea Clinton. We work with health systems across the U.S. and have expanded internationally to the MENA region, where we are partnering with healthcare organizations to deploy our AI-powered care navigation platform.

We’re hiring a Product Manager for Agent Intelligence to own the systems that measure, understand, and improve agent performance. This is a high-ownership role at the intersection of product, data, evaluation, and AI quality. You will define the roadmap for the intelligence layer that turns agent interactions into structured insights, reliable evaluations, and product improvements. You’ll partner closely with engineering, design, operations, customer teams, and other product leads to define quality standards, identify failure patterns, and close the loop between real-world conversations and better agent behavior. This role is ideal for a product manager who is excited to build 0-to-1 systems, work with large-scale conversational data, and create the foundation for agents that become more accurate, reliable, and effective over time.

Requirements

• Experience as a Product Manager, ideally working on technical, data-intensive, AI, automation, or platform products.
• Strong analytical skills and comfort working with data, metrics, and ambiguous problem spaces.
• Ability to define quality standards, measurement frameworks, evaluation processes, or operational workflows.
• Experience working closely with engineering and cross-functional teams.
• Strong written and verbal communication skills.
• Ability to turn messy, unstructured information into clear product direction.
• High ownership mindset and ability to drive both strategy and execution.

Nice To Haves

• Experience with AI products, conversational interfaces, LLMs, machine learning workflows, or agent systems.
• Experience with evaluation frameworks, experimentation, quality operations, or human-in-the-loop systems.
• Familiarity with retrieval, ranking, personalization, feedback loops, or data labeling workflows.
• Experience working with large-scale conversational, support, call, or customer interaction data.
• Experience in healthcare, senior care, care operations, or regulated environments.
• Experience building 0-to-1 products or internal platforms in a fast-moving startup environment.

Responsibilities

• Define Agent Quality: Create evaluation rubrics for agent calls and conversations, including correctness, completeness, workflow adherence, customer experience, and outcome quality. Establish scoring standards that work across workflows, customers, and use cases. Define what “good” looks like for both individual interactions and overall agent performance.
• Build Evaluation Systems: Own the systems and processes used to measure agent performance. Develop human-in-the-loop review workflows, automated evaluation pipelines, and scenario-based testing. Help Sage Care and its customers understand where agents are performing well, where they are failing, and why.
• Turn Conversations into Insights: Build ways to analyze, cluster, and explore large volumes of conversational data. Identify recurring issues, edge cases, workflow gaps, and opportunities for improvement. Translate raw interaction data into clear product insights and prioritization inputs.
• Close the Feedback Loop: Convert failures into test scenarios, product requirements, training examples, and improvement opportunities. Partner with product, engineering, and operations teams to make sure insights lead to action. Track whether product changes improve agent performance, reliability, and customer outcomes.
• Advance Learning Systems: Work on retrieval, ranking, personalization, and feedback systems that make agents more effective. Help build the foundations for agents that learn from usage, customer feedback, and operational review. Identify opportunities to use automation and AI to improve evaluation, quality monitoring, and product development workflows.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed