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Senior Product Manager (Artificial Intelligence)
Fabrichealth
New York CityHybrid1w ago
- Employment
- Full-time
- Seniority
- Senior
About the role
- 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.
- Scale the AI features already in production. Measure impact rigorously, iterate on both the model and the user experience, and expand to new use cases as evidence comes in.
- Define and operationalize the quality bar for AI in a clinical context. This includes evals, safety thresholds, hallucination guardrails, and the operational playbook for shipping responsibly.
- Make build-versus-buy decisions on models, vendors, and infrastructure. Own the tradeoffs between latency, cost, accuracy, and risk, and make them transparently.
- Set the operating cadence for AI product work: 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.
- 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 believe AI in healthcare has to be safer than AI elsewhere, and you have operational ideas about how to make that real, not just rhetorical.
- You move fast in ambiguous environments. You would rather ship a thoughtful 70% solution this quarter than wait for the perfect 95% one next year.
- You enjoy partnering with clinicians and engineers in equal measure, and you make both groups better at their jobs by working with you.
- You have not actually shipped an AI feature to production users. You have consulted, you have strategized, but you have not owned a launch.
- You are looking for a fully scoped roadmap handed to you. This role requires defining the strategy, not just executing on one.
- You are uncomfortable with the level of risk that comes with shipping clinical-facing AI. We move carefully, but we do move.
- You prefer building exclusively for one type of user. This role owns both clinician and member surfaces, and you need to be energized by that range.
- 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. You speak the language and the engineers know it.
- 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.
- Healthcare or clinical product experience, particularly on surfaces used by licensed providers.
- Experience shipping consumer or patient-facing AI in regulated contexts.
- Background in machine learning, applied science, or engineering before moving into product.
- Familiarity with HIPAA, BAAs, and the operational realities of clinical software.
- Experience leading AI product work across both B2B (clinician) and B2C (member) surfaces.
- Verify the Domain: Official recruitment emails will come from addresses ending in @fabrichealth.com or @gem.com. No other domain names are legitimate.
- Official Interview Tools: We use Gem for our recruitment process and Google Meet for all video interviews. Google Meet is always the platform used for your first interview; you will never be sent a Zoom link to set up or conduct an initial interview. All interviews are conducted via video unless specifically stated by our team as an audio call. We never conduct interviews via chat, social media, Skype, or WhatsApp.
- Zoom Usage: Zoom is utilized only for specific meetings set directly by our team for purposes outside of the standard interview process (e.g., coordination or onboarding discussions). It is never the first link you will receive from us.
- Authorized Contact & Texting: Fabric will only contact you if you have submitted an application or if you are connected to a current employee who shared your information with us. We will only send text messages if you have provided explicit authorization and consent, either through your application or while communicating directly with our team. If you have not explicitly authorized us to reach out, treat any SMS or unsolicited outreach as fraudulent and do not respond.
- Sensitive Data: We will ask you for sensitive personal or financial documents (ID, banking info, SSN) during the application, interview, or candidacy stages. All sensitive data is handled through secure internal systems post-offer.
- Verify the Team: You can reference LinkedIn to verify members of our recruiting team; however, please remain vigilant as scammers may create fraudulent profiles. Always cross-reference the sender's email domain with our official @fabrichealth.com address.
Perks & benefits
- 401k
- Unlimited Vacation
- Paid Time Off
- Equity Compensation
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