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Oracle · 4 months ago

Principal Product Manager - Clinical AI Agents

United States

Full-time

Remote

Senior Level, Lead/Staff

3+ years exp

Oracle is seeking a highly motivated Principal Product Manager to drive the end-to-end development of Clinical AI Agents. This role involves working closely with data science, engineering, and UX teams to explore opportunities, define training data requirements, and ensure the delivery of safe and effective AI solutions in healthcare.

Data GovernanceData ManagementEnterprise SoftwareInformation TechnologySaaSSoftware

No H1B

Security Clearance Required

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

Qualification

Product ManagementAI/ML Product DeliveryClinical WorkflowsLarge DatasetsData Privacy ComplianceGenerative AIUser Engagement MetricsDegreeCollaboration Skills