Hih Product Management Advisor Hyderabad (India)

Were a small AI-native RD team inside one of the largest health organizations in the country. We build products that affect real healthcare outcomes how risk gets detected, how care decisions get made, and how clinical teams do their work. Were looking for hybrid builders who own what they build: people who decide what to build, not just how. AI fluency isnt nice-to-have. Its how we work. A few honest things about this team: we have access to clinical data at a scale that would take a startup year to build through partnerships, and the ability to deploy to millions of people from day one. We also sit inside an enterprise, which means some things take longer than they would at a seed-stage company. Weve structured the team to minimize that friction and were direct about where it still shows up. The Problems Were Solving Turning overwhelming data into clarity. Large organizations generate more signals than any team can manually process. A leadership team responsible for a portfolio of millions needs to know which three trends demand attention this week and why theyre happening before manual reports would surface them. We build systems that find what matters, understand why it matters, and tell the story to the people who need to act in near-real-time, not weeks later. The technical challenge is multi-layered: anomaly detection, causal reasoning, natural language synthesis. The human challenge is harder: making AI-generated insight compelling and trustworthy enough that people actually change what they do. Clinical AI that reaches real patients. The patients who most need intervention are often invisible until theyre already in crisis. We build tools that help care teams identify who needs attentionnow turning clinical data into prioritized, actionable signals for the people making care decisions. The data is messy, the stakes are real, and getting it wrong matters. Rapid prototypes that drive real decisions. Recent AI prospects surface constantly. L .