Lead Principal Platform Software Engineer

Oracle Oracle · Enterprise · United States

Lead Principal Platform Software Engineer to architect and build an AI harness and toolkit for enterprise partners, enabling them to develop and integrate AI-powered applications. The role focuses on platform capabilities, developer experience, AI integrations, evaluation workflows, and application enablement, requiring strong platform engineering, architectural judgment, and practical experience with AI/LLMs in production.

What you'd actually do

  1. Architect and evolve core platform capabilities for AI-assisted application development.
  2. Design scalable, secure, and reliable services, APIs, SDKs, and integration patterns for GIU partner teams.
  3. Lead technical strategy for AI harness capabilities, including LLM integration, prompt orchestration, evaluation workflows, agentic development patterns, and reusable AI components.
  4. Define platform standards for observability, reliability, security, testing, performance, and operational readiness.
  5. Partner with GIU engineering teams to understand adoption needs and translate them into reusable platform features.

Skills

Required

  • Deep platform engineering expertise
  • Strong architectural judgment
  • Practical experience applying AI and LLM technologies in production-oriented environments
  • Lead through technical influence
  • Mentor senior engineers
  • Define scalable implementation patterns
  • Establish standards for AI-enabled applications
  • Broad systems thinking
  • Build platforms that other engineers love to use
  • Operate effectively in ambiguous, fast-moving technical domains
  • Frontend technologies: JavaScript, TypeScript, nodejs

Nice to have

  • Deep technical knowledge of frontend technologies

What the JD emphasized

  • AI harness and toolkit
  • AI-powered application experiences
  • enterprise standards
  • AI integrations
  • evaluation workflows
  • agentic development patterns

Other signals

  • AI harness and toolkit
  • develop, integrate, and deliver AI-powered application experiences
  • reusable capabilities, patterns, and tooling
  • enterprise standards for quality, reliability, security, and maintainability
  • LLM integration, prompt orchestration, evaluation workflows, agentic development patterns, and reusable AI components