Sr. Product Manager, Enterprise AI

About the Role

Hinge Health is hiring a Senior Product Manager to build AI-powered products that improve how our teams serve and operate  will lead the strategy and execution for enterprise AI capabilities across operational functions, including Client Success, Member Services, Revenue Operations. Your work will focus on turning complex, manual, and fragmented processes into reliable, measurable workflows while strengthening the data and platform foundations required to scale them.

This role combines product strategy, workflow design, applied AI, data infrastructure, and cross-functional execution. You will partner closely with Engineering, Data, Design, and operational teams to identify high-value opportunities, launch solutions incrementally, and measure their impact. You will also help shape self‑service and client‑facing experiences that make it easier for users to engage with Hinge Health.

• Define and lead the product strategy and roadmap for enterprise AI, workflow automation, and supporting data capabilities across member, client, revenue, and business operations.

• Identify high‑value operational problems and translate them into clear product requirements, experiments, and phased releases.

• Develop AI‑powered workflows that reduce administrative burden, improve consistency, and enable operational teams to focus on higher‑value member and client needs.

• Partner with operational teams to standardize processes, metrics, templates, and playbooks so they can be automated, measured, and continuously improved.

• Improve workflows across the member and client lifecycle, including member support, client onboarding, account management, revenue operations, reporting, issue resolution, and ongoing engagement.

• Work with Engineering, Data, and Design to build reliable integrations and intelligent workflows across systems such as CRM, customer success platforms, member support tools, communications, scheduling, billing, and analytics platforms.

• Define quality standards and evaluation frameworks for AI‑powered features, including accuracy, reliability, human review, failure handling, and ongoing performance monitoring.

• Establish data contracts, instrumentation, governance, and operational standards that make products auditable, extensible, and resilient.

• Build appropriate privacy, security, and access controls into enterprise AI experiences involving sensitive member, client, and commercial data.

• Create a durable product operating cadence across discovery, prioritization, backlog management, stakeholder reviews, launches, and post‑launch measurement.

• Define success metrics and use qualitative and quantitative evidence to evaluate adoption, time savings, service quality, member and client experience, revenue impact, and business outcomes.

• Identify reusable platforms, shared capabilities, and common workflow patterns across operational functions.

• Communicate product decisions, tradeoffs, progress, and risks clearly to technical teams, operational leaders, and senior stakeholders.

• Stay current on developments in enterprise AI, workflow automation, data platforms, and member and client experience technology.

• 2+ years of product management experience, including ownership of enterprise software, internal platforms, workflow automation, AI‑enabled products, or products used by operational and customer‑facing teams.

• Experience taking ambiguous operational problems from discovery through launch, adoption, and measurable impact.

• Demonstrated ability to convert manual, inconsistent, or high‑friction processes into scalable product workflows.

• Experience building products for functions such as client success or sales operations, or customer service.

• Experience building products that integrate enterprise systems such as CRM, customer success, support, communications, scheduling, billing, analytics, or data platforms.

• Strong understanding of product instrumentation, observability, service‑level expectations, governance, and operational reliability.

• Experience partnering with Engineering and Data teams on APIs, integrations, data pipelines, embedded analytics, or platform capabilities.

• Ability to…