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.

Qualifications

Required

• 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.

Even Better

• 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.

What Success Looks Like

• Agent quality is clearly defined, measurable, and trusted across teams.
• Failures are identified quickly, consistently, and at scale.
• Feedback from real conversations is converted into test cases, product improvements, and learning loops.
• Product and engineering teams can see whether changes improve agent performance.
• Sage Care agents become more accurate, reliable, and effective over time.

Why This Role Matters

Agent Intelligence is a core part of Sage Care’s product advantage. As our agents handle more complex conversations, the ability to measure performance, detect failures, and improve continuously becomes essential to delivering safe, reliable, and high-quality care navigation.

This role is responsible for building the system that helps Sage Care understand and improve every agent interaction.

How We Work

At Sage Care, our values shape how we build, collaborate, and serve.

• Do Good Through Serving People: We serve users, teammates, and communities with integrity, compassion, kindness, and optimism.
• Innovate with Safety, Evidence, and Transparency: We move quickly while prioritizing trust, safety, ethical decision-making, and evidence-based approaches.
• Lead with Curiosity and Kindness: We ask questions before making assumptions and approach discovery, debate, and problem-solving with humility and care.
• We, Not Me: We believe the best work happens through collaboration, mutual respect, and constructive feedback.
• Efficiency and AI in All We Do: We use automation and AI thoughtfully to work smarter, create leverage, and build better products.

Compensation: $150K - $185K