Senior Software Engineer 3 – Oracle Labs & Experiences (Oracle Labs)

Company: Oracle

Location: Location not specified (Remote)

Remote: Yes

Posted: 2026-01-31

About this role

Job Description
What you’ll do

  • Design and build new Oracle-based labs and demos that showcase AI/ML, data, and application services through realistic, scenario-driven use cases (e.g., RAG pipelines, AI agents, or data ingestion workflows).
  • Write production-grade code (Python, Bash, Terraform, SQL, etc.) to implement backend logic, automation, APIs, and orchestration used within labs.
  • Develop interactive Markdown-based lab instructions, templates, and reusable modules that deliver a consistent, high-quality learner experience.
  • Break down complex Oracle and AI concepts into clear, incremental steps that can be easily followed by users of varying technical skill levels.
  • Prototype, deploy, and validate labs end-to-end—focusing on usability, reliability, performance, and documentation quality.
  • Collaborate with product and field teams to align labs with new Oracle releases, GenAI platform features, and customer-requested topics.
  • Build and maintain reference architectures and SDK examples that demonstrate integration of OCI GenAI Services, AI Vector Search, and Oracle Database.
  • Participate in live demos, dry runs, and internal enablement to showcase labs and gather feedback from engineers and customers.
  • Mentor junior Cloud Engineers and guide best practices for lab development, testing, and delivery.

Core focus areas

  • Lab & Demo Development: Workshop authoring, event code setup, Terraform automation, OCI SDK integration, markdown-based instruction design.
  • AI/GenAI Workloads: RAG pipelines, embeddings/vector search, agentic workflows, and GenAI API orchestration.
  • OCI Services: Data Flow (Spark), Streaming/Kafka, Object Storage, Functions, OKE, AI Vector Search, IAM/Vault, and networking.
  • Oracle Database Integration: Autonomous Database, JSON Duality Views, AI Vector Search, and data ingestion for AI workloads.
  • Multi-Cloud & Partner Ecosystem: Familiarity with AWS, Azure, GCP, and NVIDIA AI/cloud offerings for comparative lab design ...

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