Staff Product Manager, Clinical Monitoring & Intervention

What you'll work on

• Define the Evaluation Standard: Own the gate clinical or caregiver-facing AI features have to clear. Decide what 'ready' means and raise the bar for features to get there.
• Own Cross-Surface AI Consistency: A patient's baseline, care plan, and chart notes are read and written by both the caregiver and clinician products. Ensure that those systems reason about the same patient the same way, so a signal captured on one surface is reflected in the other.
• Set the Bar for AI Product Development: Partner closely with the PMs on other product areas to raise the standard of their AI-feature specs, their evaluation criteria, and their partnership with Applied AI.
• Partner Directly with Applied AI Leadership: Work at the architecture level on how caregiver AI and clinician AI are evaluated, monitored, and iterated post-launch.
• Build for Regulated, Clinically Critical Ground Truth: Ensure that evaluation frameworks hold up against clinical scrutiny and payer/compliance review. Partner with clinical leadership and compliance to make sure that products measured against clinician dispositions are rigorous enough to trust.

What success looks like

• Clinical or caregiver-facing AI features that reach production clear a documented shadow-mode evaluation against real dispositions.
• Caregiver-side and clinician-side AI systems can be proven to reason consistently about the same patient with no contradicting baselines or signals that are dropped at the handoff between surfaces.
• Other AI PMs at Abby Care treat your evaluation standard as the bar.

What you'll have

• Experience: 8+ years of product management experience, with a proven track record of leading complex, high-impact AI or ML product initiatives at a Staff or Lead PM level in a high-growth tech environment.
• AI Product Depth: Direct experience designing evaluation frameworks for AI systems in production and deciding how AI features' real-world performance is measured, monitored, and gated before and after launch.
• Technical Fluency: Strong technical acumen, particularly in working with engineering and Applied ML and AI teams to build data-intensive or AI-driven platforms. You don't need to write code, but you must be able to deeply evaluate technical trade-offs.
• Customer Obsession: Deep empathy for users (in our case, family caregivers and care recipients) and a rigorous approach to qualitative and quantitative research in a regulated environment.
• Relentless Resourcefulness: You thrive in fast-paced startup environments. You adapt quickly, solve challenges with creativity, and deliver results without unnecessary complexity.
• Exceptional Communication: The ability to distill complex healthcare and technical concepts into clear, actionable product requirements and compelling strategic narratives for executive stakeholders.

Bonus / Nice to Have

• Experience in HealthTech, Medicaid waivers, or highly regulated industries where AI decisions carry compliance or clinical-safety weight.
• A strong background working with LLMs, machine learning, or AI-native consumer products.
• Previous experience navigating a marketplace or labor-supply business model (e.g., gig economy, digital health).