Product Manager, AI Devices

Responsibilities

• Own the AI-Driven Roadmap: Define and manage the detailed product roadmaps for new AI products across X-ray, CT, MRI, and Ultrasound—from initial concept through launch sequencing and ongoing iteration.
• Drive Modality Deployments: Lead end-to-end deployment of new AI products for each modality, coordinating cross-functional readiness across AI, clinical quality, clinical operations, data, and engineering.
• Own Data Product Requirements: Partner closely with Data Engineering to define requirements for data quality, preprocessing pipelines, storage, and architecture that enable reliable model training and production performance.
• Facilitate Cross-Functional Execution: Serve as the day-to-day connector between AI, clinical quality, clinical operations, and data teams—helping lead recurring forums to align on decisions, unblock issues, and maintain momentum.
• Manage Timelines and Resourcing: Build and maintain integrated timelines and resource plans, including headcount needs and key OPEX inputs (compute, storage, and data transfer), surfacing tradeoffs early.
• Build the User Feedback Loop: Establish a repeatable process to gather user feedback post-deployment and translate it into a prioritized backlog of product improvements and experiments.
• Define and Analyze Performance Metrics: Establish KPIs and dashboards to evaluate product performance, quantify operational impact, and package results for leadership, board, investors, and marketing narratives.

Qualifications

• 3-6 years of experience in product management, preferably with a focus on healthcare software/platform products.
• Problem-Solving Mindset: A proven track record of breaking down complex problems and driving to elegant solutions.
• Technical Product Execution: Demonstrated experience in an agile/scrum development environment, with a strong ability to write clear requirements and manage a backlog.
• Technical AI Fluency: Sufficiently technical to understand system architectures and basic AI/Machine Learning concepts.
• Data & Analytics Mastery: Demonstrated ability to analyze complex datasets to derive actionable insights regarding user behavior and operational efficiency.
• Stakeholder Management: Exceptional ability to manage cross-functional processes and communicate effectively with both high-level stakeholders and engineering teams.
• Platform Leadership: Experience driving a platform backlog and setting quarterly roadmaps that align with broad company objectives.
• Healthcare Domain Knowledge: Familiarity with healthcare-specific standards (DICOM, HL7) and imaging systems (PACS, VNA) is highly preferred.

Compensation: Base salary $125,000 - $175,000, plus equity, performance-based bonus, and benefits.