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DocPlanner is a global healthcare platform connecting 300,000+ doctors with 100 million patients monthly across 13 markets. Noa, its AI-driven product line, helps doctors remove administrative work, make better clinical decisions, and helps patients navigate healthcare with personalized context.
You'll serve as the first dedicated clinical product hire, bridging clinical expertise, product strategy, and AI development. This is a hands-on role combining clinician, product manager, and AI specialist perspectives.
Key responsibilities:
SHAPE WHAT WE BUILD: Bring authentic doctor workflows, habits, and preferences into product decisions. Conduct peer-to-peer interviews with doctors to uncover honest feedback. Partner with Product on roadmap prioritization based on real clinical needs and adoption likelihood.
MAKE SURE IT'S CLINICALLY SOUND: Define clinical quality standards and intended outcomes for AI products. Review and refine prompts, model outputs, clinical templates, workflows, and medical terminology. Identify clinical failure modes and acceptable/unacceptable outputs. Direct clinical evaluation—decide what to test, which specialties/populations/edge cases to cover, and set quality thresholds. Bootstrap a dedicated clinical evaluation owner who manages annotation processes and guidelines. Convert model errors and clinician feedback into concrete product and model improvements.
KEEP IT SAFE AND SCALABLE: Collaborate with ML/LLM teams, regulatory experts, and the Product Risk & Regulatory Committee to align intent, evidence, risks, and controls (including EU MDR compliance). Build feedback loops with practicing clinicians and consultant networks. Define how clinical expertise scales across future products, teams, and markets.
Required qualifications: Medical degree with meaningful clinical practice experience. Understanding of clinicians' day-to-day workflows. Track record building and shipping digital health, clinical software, or AI products (product team or entrepreneurial). Ability to translate clinical problems into product decisions, not just advisory input. Strong clinical judgment that translates quality/safety into technical standards. Ability to quickly earn doctors' trust as a peer. Clear communication across clinical, product, technical, regulatory, and leadership stakeholders. Comfortable working at senior, hands-on level in fast-moving international teams. Active generative AI user with understanding of potential and limitations.
Bonus: Experience with ambient documentation, clinical templates, medical-knowledge systems, clinical coding, evaluation datasets, or regulated Software as a Medical Device (SaMD) certification.
Success metrics (6 months): Clinical quality framework for priority AI products in place. Clinically grounded evaluation sets and thresholds established. Repeatable process to convert medical expertise into better product and model decisions.
