Group Product Manager, AI & Clinical Intelligence
E
EquipHealth Tech
Remote - USAFull-TimeManager
Salary$148K - $185K; $148K – $185K • Offers Bonus
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Job Details
- Experience
- 8+ years
- Required Skills
- Data AnalysisProduct ManagementCross-functional Team LeadershipHIPAA
Requirements
- 8+ years of product management, including significant AI/ML experience in regulated or clinically sensitive domains.
- Strong technical fluency in AI/ML (e.g., model evaluation, RAG, guardrails) to partner effectively with engineering.
- Experience building products for clinical workflows and healthcare operations.
- Expertise in healthcare regulatory requirements (e.g., HIPAA, clinical decision support standards).
- Comfort navigating ambiguity to establish AI guardrails in clinical settings.
- Ability to lead cross-functional teams and translate requirements between clinical, technical, and executive stakeholders.
- Data-driven approach to measuring product performance, clinical impact, and safety outcomes.
Responsibilities
- Own the product roadmap for AI and clinical intelligence capabilities, aligning it with clinical outcomes goals, company strategy, and regulatory requirements.
- Partner closely with AI/ML engineers to scope, prioritize, and ship models and features — translating clinical requirements into technical specifications and translating technical constraints back into clinically sound product decisions.
- Collaborate with clinical leadership (therapists, dietitians, medical providers) to ensure AI-assisted tools reflect gold-standard eating disorder treatment practices and do not introduce clinical risk.
- Define and govern responsible AI practices for clinical use cases, including model evaluation criteria, human-in-the-loop safeguards, escalation paths, and bias/safety monitoring appropriate to a clinically sensitive population.
- Design and oversee analytics and evaluation frameworks that measure model performance, clinical impact, and patient/provider trust — not just usage.
- Guide AI product development through the full lifecycle: problem framing, model/vendor evaluation, prototyping, clinical validation, launch, and iteration.
- Translate healthcare regulations and compliance requirements (HIPAA, informed consent, clinical documentation standards) into product and model requirements.
- Conduct research with patients, providers, and clinical staff to identify where AI can responsibly reduce burden or improve care, and where it should not be applied.
- Present AI product strategy, risk considerations, and results to executive leadership, clinical leadership, and the board as needed.
- Mentor and potentially build out a small team of PMs focused on AI/clinical intelligence workstreams.
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