Lead Principal Product Manager

Oracle Oracle · Enterprise · United States

Product Manager for a next-generation Life Sciences Intelligence Suite, an AI-powered platform focused on improving outcomes through data-driven decisions, trial optimization, and safety actions. The role involves shaping and driving a modern, agentic SaaS platform that unifies clinical, safety, and commercial applications into an intelligence ecosystem. Key responsibilities include defining product vision and strategy, leading AI-first product development, championing post-market workflows, shaping platform architecture, and partnering with engineering and data science teams.

What you'd actually do

  1. Own the product strategy for Oracle’s Life Sciences Intelligence Suite, aligning long-term vision with real customer needs across post-market, safety and evidence generation domains.
  2. Drive AI-first 0-1 product development, leading the evolution from form-based legacy workflows to intelligent, agentic applications that surface insights and drive actions.
  3. Champion end-to-end post-market workflows with pharma, health systems and payers — from market intelligence, safety actions, and post-trial commercialization.
  4. Shape platform architecture and experience, ensuring seamless integration between pharma sponsors, provider sites, and analytics teams.
  5. Partner deeply with engineering, data science, and cloud infrastructure teams to translate advanced AI capabilities into trusted, scalable products.

Skills

Required

  • 10+ years of product management experience in healthcare and life sciences, healthcare technology, agentic AI and enterprise SaaS.
  • Proven success leading platform-level strategies that unify complex, siloed systems.
  • Deep understanding of one or more of these areas - digital health, clinical trial operations, pharmacovigilance, and real-world data ecosystems.
  • Strong foundation in AI and agent-based systems with practical understanding of healthcare data flows and architectures.
  • Experience working in highly regulated environments, including privacy, security, and compliance frameworks.

Nice to have

  • Agentic AI and autonomous workflow design
  • Digital health to drive better patient outcomes
  • Trial optimization and clinical operations platforms
  • Real-world data, outcomes research, and evidence generation
  • SaaS product development in regulated industries
  • Health equity and population health integration into life sciences strategy.

What the JD emphasized

  • agentic SaaS platform
  • agentic applications and workloads
  • AI and agent-based systems

Other signals

  • agentic SaaS platform
  • AI-first 0-1 product development
  • agentic applications and workloads