RA Lead

Technical Product Manager – Healthcare

Required Experience

• 5+ years in technology product or platform product roles.
• Demonstrated experience delivering healthcare technology products.
• Direct exposure to healthcare data, analytics, or AI-enabled solutions.
• Experience operating in regulated environments, including HIPAA, PHI, and healthcare compliance.
• Proven ability to lead complex healthcare initiatives through ambiguity and change.

Healthcare Domain Expertise

• Strong understanding of healthcare operations and workflows, including:
• Payer
• Provider
• Care Management
• Familiarity with healthcare domains such as:
• Utilization Management (UM)
• Care Management / Case Management
• Prior Authorization
• Ability to translate clinical and operational workflows into scalable technology solutions.
• Strong understanding of regulatory, compliance, and patient safety considerations in product decisions.

Product & Strategy

• Outcome-driven product mindset grounded in healthcare realities and AI/data-first thinking.
• Ability to identify where data, analytics, and AI can improve healthcare outcomes or reduce administrative burden.
• Roadmap ownership integrating:
• Core healthcare capabilities
• Data and interoperability foundations
• Analytics and AI enablement
• Prioritization informed by:
• Clinical impact
• Operational value
• Feasibility
• Risk
• Strong problem framing focused on insight generation, automation, and scale.

Data, Analytics & AI Enablement

• Working understanding of:
• Healthcare data domains, including member, provider, clinical, authorization, and outcomes data.
• Data flows across payer, provider, and partner systems.
• Ability to partner with Data Engineering, Analytics, and AI teams to:
• Enable reliable healthcare analytics and reporting.
• Support decision-making through insights and AI-assisted summarization.
• Experience defining requirements for:
• Operational and clinical dashboards.
• KPIs tied to quality, efficiency, cost, and experience.
• AI-enabled analytics, including summarization, prioritization, and decision support.
• Awareness of data quality, lineage, interoperability, and adoption challenges in healthcare.

AI & Automation in Healthcare

• Understanding of AI use cases relevant to healthcare:
• Clinical and operational summarization.
• Decision support with human-in-the-loop.
• Workflow automation and prioritization.
• Ability to balance innovation with:
• Responsible AI practices.
• Explainability and auditability.
• Regulatory and ethical considerations.
• Experience guiding AI from pilot to production to scaled adoption in healthcare settings.

Technology & Architecture Knowledge

• Understanding of modern architectures supporting healthcare data and AI:
• APIs
• Microservices
• Cloud platforms
• Data platforms
• Interoperability layers
• Integration patterns
• Ability to evaluate build vs. buy vs. reuse with healthcare constraints in mind.
• Comfort navigating legacy systems, technical debt, and complex integrations common in healthcare ecosystems.

Delivery & Execution

• Agile / SAFe execution with emphasis on progress, readiness, and adoption.
• Strong dependency and risk management across:
• Product teams
• Data pipelines
• Analytics platforms
• AI platforms
• Release planning that includes:
• Data readiness and validation.
• Analytics accuracy.
• AI model monitoring.
• Compliance checks.

Stakeholder & Communication

• Trusted partner to business, clinical, and operations leaders.
• Clear articulation of trade-offs, risks, and value realization.