Principal Backend Developer – Clinical Applications

Oracle Oracle · Enterprise · United States

This role is for a Principal Backend Developer focused on building and modernizing Electronic Health Record (EHR) applications within Oracle Health. The primary focus is on backend development, distributed systems, and scalable cloud-native architecture for clinical applications, provider workflows, and messaging. While the role leverages AI-assisted development tools for productivity and collaborates with AI-powered healthcare capability teams, the core responsibility is application engineering and platform delivery, not direct AI/ML model development.

What you'd actually do

  1. Design, develop, and maintain cloud-native EHR applications supporting clinical inbox, messaging, and provider workflow experiences.
  2. Build highly scalable backend services and distributed systems that power critical healthcare workflows.
  3. Develop full-stack solutions while maintaining a primary focus on backend architecture, performance, reliability, and scalability.
  4. Serve as a technical leader within the team, helping guide architecture decisions and engineering best practices.
  5. Own services and applications throughout the entire development lifecycle, from requirements gathering through deployment and production support.

Skills

Required

  • Java, Python, or other object-oriented programming languages
  • distributed systems
  • microservices architecture
  • APIs
  • scalability
  • resiliency
  • performance optimization
  • cloud-native applications
  • technical lead experience
  • mentoring engineers
  • software design principles
  • data structures
  • algorithms
  • system architecture
  • communication skills

Nice to have

  • cloud platforms
  • containerization
  • modern DevOps practices
  • highly regulated environments
  • AI-assisted development tools
  • GitHub Copilot
  • Codex

What the JD emphasized

  • strong backend expertise
  • deep backend expertise
  • strong software engineering fundamentals
  • independent problem-solving capabilities
  • strong technical depth rather than reliance on AI-generated code
  • full understanding of system design and implementation details