Lead Principal Platform Software Engineer

Oracle Oracle · Enterprise · United States

Lead Principal Platform Software Engineer to design and build scalable platforms, automation, and agentic AI-driven solutions for incident management in Oracle Cloud Infrastructure, aiming to improve detection, investigation, mitigation, and learning from service-impacting events.

What you'd actually do

  1. Design and deliver scalable systems, services, and automation that improve OCI-wide reliability.
  2. Lead agentic and AI-powered solutions that accelerate incident detection, diagnosis, mitigation, and learning.
  3. Define architectural patterns, engineering standards, and observability practices that improve resiliency and operability.
  4. Lead complex cross-organizational initiatives with broad customer and business impact.
  5. Serve as a technical leader during critical incidents, driving systemic fixes and long-term improvements.

Skills

Required

  • Bachelor’s degree in Computer Science or related field, or equivalent practical experience.
  • 10+ years of software development experience.
  • Strong proficiency in one or more modern languages such as Java, C++, Go, or Python.
  • Experience designing and building large-scale distributed or cloud systems.
  • Experience with observability, testing, CI/CD, and production operations.
  • Strong software engineering fundamentals and architecture skills.

Nice to have

  • Experience with incident management, SRE, or cloud operations.
  • Experience applying AI, LLMs, or agentic systems to automation workflows.
  • Strong communication, leadership, and cross-functional influence.
  • Experience mentoring engineers and driving organization-wide technical improvements.
  • Experience with OCI or other large-scale cloud platforms.

What the JD emphasized

  • agentic AI-driven solutions
  • accelerate incident detection, diagnosis, mitigation, and learning
  • applying AI, LLMs, or agentic systems to automation workflows

Other signals

  • agentic AI-driven solutions
  • accelerate incident detection, diagnosis, mitigation, and learning
  • applying AI, LLMs, or agentic systems to automation workflows