Principal Product Manager- Healthcare AI

Principal Product Manager- Healthcare AI at Oracle

The Oracle Clinical AI Agent team's mission is to deliver an AI platform that serves as the foundation for Oracle's health applications. By embedding generative and conversational AI into these applications, we empower clinicians to simplify their workflows, reduce manual tasks, and focus more on patient care. Our diverse team of innovators is building the future of conversational clinical interfaces—improving the lives of patients and providers worldwide. We work with the agility of a start-up and the impact of an industry leader. Join us and shape the future of healthcare.

We are seeking a highly motivated Principal Product Manager to drive the end-to-end development of Clinical AI Agents—from concept to release. In this role, you will work closely with data science, engineering, and UX to explore new opportunity spaces, define gold-standard training data requirements, guide the model development lifecycle, and ensure the delivery of safe, effective, and clinically useful AI agents.

Your Qualifications:

• 7+ years of professional experience in product management
• 2+ years of experience delivering AI/ML products, ideally in multiple industries
• Familiarity with large datasets, analytics, and user engagement metrics
• Experience in clinical workflows and regulated healthcare environments is preferred
• Knowledge of data privacy and compliance requirements within healthcare settings is advantageous

Preferred Qualifications:

• Experience with Generative AI and AI frameworks
• Demonstrated success launching 0-to-1 products and achieving market traction
• A bachelor’s degree in Computer Science, Engineering, or equivalent experience

Join us to shape the future of healthcare, transforming how clinicians deliver care through AI-driven solutions that enhance efficiency, reduce burnout, and improve patient outcomes.

Responsibilities:

• Define Product Strategy & Roadmap: Craft and maintain product roadmaps focused on delivering engaging, user-centric features that encourage clinicians and healthcare staff to adopt AI-powered capabilities in their daily workflows.
• Apply AI & Emerging Technologies: Stay current with advances in NLP, large language models, and generative AI. Adapt these technologies to streamline clinical workflows, differentiate from competitors, and deliver measurable improvements in efficiency and patient outcomes.
• Define and Explore Opportunity Areas: Partner with clinicians, researchers, and internal stakeholders to identify high-value clinical workflows that can be transformed using AI agents.
• Lead Concept Development: Translate abstract ideas and unmet needs into structured product concepts, defining the problem space, success criteria, and technical feasibility.
• Collaborate Across Functions: Work hand-in-hand with data science, engineering, and UX teams to shape agent behavior, training strategies, and user experience.
• Gold Data Strategy & Acquisition: Drive the creation and curation of high-quality, representative datasets required for training and validating agent models, including annotation guidelines and domain coverage.
• Model Development Oversight: Coordinate the training, tuning, and evaluation of models—ensuring alignment with clinical intent, performance benchmarks, and compliance standards.
• Validation & Safety Testing: Develop validation protocols to test agent performance, usability, and clinical safety in real-world-like environments prior to release.
• Product Readiness & Delivery: Collaborate on release planning, documentation, and internal enablement to support the smooth launch of new agent capabilities.
• Compliance & Risk Awareness: Ensure that Clinical AI Agents meet healthcare industry standards for data privacy, transparency, and reliability.
• Customer Engagement & Feedback Loops: Identify lead customers, cultivate design partnerships, and incorporate direct user feedback to validate assumptions, guide product evolution, and ensure clinical needs remain at the forefront of innovation.

Key skills/competency:

• Product Management
• AI/ML Product Development
• Healthcare Workflows
• Generative AI
• NLP (Natural Language Processing)
• Large Language Models
• Data Privacy
• Compliance
• UX Collaboration
• Stakeholder Management