Lead Principal Application Software Engineer- Oracle Health

Oracle Oracle · Enterprise · United States

Lead Principal Application Software Engineer for Oracle Health AI, focusing on building automation, orchestration, and AI-powered capabilities for customer onboarding. The role involves designing and developing cloud-native services, scalable automation, and orchestration frameworks, with a strong emphasis on integrating AI/LLMs into platform capabilities to automate workflows and decision-making.

What you'd actually do

  1. Design and build cloud-native services and distributed systems on OCI.
  2. Develop scalable automation for customer onboarding, provisioning, deployments, migrations, and lifecycle management.
  3. Build orchestration frameworks that enable touchless customer onboarding.
  4. Build AI-powered capabilities that automate onboarding workflows and operational decision making.
  5. Improve platform reliability through observability, telemetry, monitoring, and self-healing.

Skills

Required

  • Bachelor's degree in Computer Science or equivalent practical experience.
  • 10+ years designing and operating large-scale cloud-native distributed systems.
  • Strong programming skills in Java, Go, Python, C++, C#, or similar languages.
  • Experience with microservices, REST APIs, Kubernetes, Terraform, Infrastructure as Code, and cloud orchestration.
  • Experience building scalable infrastructure software or automation platforms.
  • Experience with OCI, AWS, Azure, GCP, or equivalent cloud platforms.
  • Proficiency using AI-assisted development tools such as Oracle Code Assist (CodeX), Claude Code, GitHub Copilot, Cursor, or equivalent.
  • Hands-on experience building AI-enabled solutions using LLMs, AI agents, RAG, MCP, vector databases, and prompt engineering.
  • Ability to apply AI to automate engineering workflows, customer onboarding, infrastructure operations, and developer productivity.
  • Strong analytical, troubleshooting, communication, and leadership skills.

Nice to have

  • Agile/Scrum experience.
  • Cloud control planes or workflow orchestration experience.
  • Fleet management or environment lifecycle management.
  • Observability platforms, networking, storage, cloud security.
  • Technical leadership across multiple teams.
  • Machine Learning fundamentals and MLOps.
  • Experience building AI-native applications or autonomous engineering workflows.

What the JD emphasized

  • Hands-on experience building AI-enabled solutions using LLMs, AI agents, RAG, MCP, vector databases, and prompt engineering.
  • Ability to apply AI to automate engineering workflows, customer onboarding, infrastructure operations, and developer productivity.

Other signals

  • building AI-powered capabilities
  • hands-on experience building AI-enabled solutions
  • apply AI to automate engineering workflows