Fabrichealth

Senior Product Manager (Artificial Intelligence)

New York, USA · Senior

Sponsorship not specified$140k-$165kDetected 44 days ago

Machine LearningLLMsRAGComplianceProduct ManagementProduct StrategyCadenceHIPAALeadership

About the role

We have shipped our first AI features into production.
If you have shipped LLM or ML-powered products to real users and you want to do it where the work compounds for clinicians and patients, you will thrive here.

As the Senior Product Manager, AI, you will own the AI product strategy and execution for Fabric across both clinician-facing and member-facing surfaces.
Your primary responsibilities will include: Own the product strategy and roadmap for AI experiences across clinician-facing and member-facing surfaces, with clear bets, sequencing, and success criteria.
Partner with engineering, applied ML, design, and clinical leadership to ship AI products that move the metrics that matter: clinician time recovered, member activation, care outcomes, cost to serve.
Make build-versus-buy decisions on models, vendors, and infrastructure.
Own the tradeoffs between latency, cost, accuracy, and risk, and make them transparently.

6+ years of product management experience, with at least 2 years owning AI or ML-powered products in production.
A track record of shipping LLM, ML, or AI-powered features to real users at meaningful scale.
Strong working knowledge of LLM fundamentals: evals, prompting, RAG, fine-tuning tradeoffs, and the latency-cost-accuracy curves that shape every real-world deployment.
Proven partnership with applied ML, AI infrastructure, or engineering teams.
Comfort operating in regulated environments where safety, accuracy, and audit-readiness are not optional.
Excellent product judgment and the ability to make calls in ambiguity without waiting for permission.
Experience shipping consumer or patient-facing AI in regulated contexts.
Familiarity with HIPAA, BAAs, and the operational realities of clinical software.
Experience leading AI product work across both B2B (clinician) and B2C (member) surfaces.

how experiments run, how we measure, how we ship safely, and how we communicate AI risk and reward to clinical and executive stakeholders.
Translate between technical ML capability and clinical workflow reality.
Neither side wants to learn the other side's language, and your job is to bridge it.
Why You Might Be a Good Fit You have shipped LLM or ML-powered products to real production users, ideally on a clinician-facing or consumer-facing surface, and you can talk about what worked and what did not.
You think in evals, not in vibes.
You know how to define a quality bar for an AI feature and instrument against it.
You are fluent enough in the underlying ML stack that engineers respect you, you can call BS on vendor claims, and you can hold a real conversation about model selection, RAG, fine-tuning, latency, and cost.
You move fast in ambiguous environments.

Bonus Points Healthcare or clinical product experience, particularly on surfaces used by licensed providers.
Background in machine learning, applied science, or engineering before moving into product.
Certain roles may also be eligible for additional compensation, including a comprehensive benefits package such as medical, dental, vision, unlimited PTO, and a 401(k) plan, stock options and bonuses.

This listing is sourced directly from Fabrichealth's careers page and normalized into a canonical job model.