SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Qualified Health is seeking a Senior AI Product Manager to own the data, analytics, evaluation, and governance core of their healthcare AI platform. This is an integrator and enabler role focused on creating connective tissue across the data platform, analytics, and platform engineering teams—not a control role, but one that removes coordination friction and accelerates delivery.
You will own the data layer as a product, defining serving contracts, gold-layer marts, and semantic views consumed by assistants, chat, workflows, and dashboards. You'll establish analytics and insights products including customer-facing dashboards, usage analytics, cost observability, and a KPI catalog with one definition per metric and lightweight vetting. For clinical products like Care Gap Optimizers, you'll define data and scoring pipelines with clear acceptance criteria and generalization requirements before build begins.
Evaluation becomes a shared platform capability under your ownership—frameworks, datasets, and gates that determine whether AI outputs are safe to ship and remain safe in production. Governance, the platform's spine and differentiator, transitions from a checklist to a product surface with clear controls and auditable evidence for healthcare compliance.
Key responsibilities include owning the roadmap for data and analytics products, mapping analytics questions to source systems and architecting how data lands in the serving layer, turning per-customer builds into reusable products with clear interfaces, defining generalization requirements for scored outputs, writing complete acceptance criteria before sprints, running vetting for customer-facing KPIs, owning cost observability as a product, and defining evaluation gates as reusable platform capability.
You'll report to the SVP of Product, sit on the Platform pod, and partner daily with the data platform lead, analytics and new product development lead, engineering leadership, and peer product managers. Success is measured by whether the data platform and analytics teams say you make them faster.
