Principal Data Systems Software Engineer

Oracle is seeking a Principal Data Systems Software Engineer (IC4) to design and build next-generation cloud-native and AI-powered capabilities for Oracle Database Cloud Platform. This role combines distributed systems engineering with modern AI application development, including Generative AI, LLMs, AI agents, and cloud-native architectures. The engineer will lead technical initiatives, influence architecture decisions, modernize platform capabilities, and develop highly scalable services running on Oracle Cloud Infrastructure.

Key Responsibilities
 

• Design, architect, and develop cloud-native services supporting Oracle Database on OCI.

• Build scalable AI-enabled platform capabilities leveraging LLMs, AI agents, RAG, and modern AI architectures.

• Design provisioning, lifecycle management, monitoring, automation, and operational frameworks for Database Cloud services.

• Collaborate with Product Management, Compute Engineering, Operations, and cross-functional Oracle engineering teams.

• Build production-grade distributed systems emphasizing scalability, resiliency, observability, and security.

• Modernize existing platform components into intelligent AI-first cloud-native services.

• Integrate enterprise systems, APIs, databases, and cloud services into AI-powered workflows.

• Troubleshoot production issues, perform root cause analysis, and provide Level 3 engineering support.

Qualifications & Skills
Mandatory
 

• Bachelor's or Master's degree in Computer Science or related discipline.

• Strong experience building distributed systems and cloud-native applications.

• Hands-on experience developing Generative AI and LLM-based applications.

• Experience with:

  • Retrieval-Augmented Generation (RAG)

  • AI Agents

  • Prompt Engineering

  • Model Orchestration

  • Vector Databases

  • Embeddings

  • AI Evaluation Frameworks

• Production experience with AI/ML pipelines and inference services.

• Experience with OCI, AWS, Azure, or GCP.

• Kubernetes, Containers, REST APIs, Serverless technologies.

• Strong Python and/or Java programming.

• Experience with OpenAI SDKs, Hugging Face, or similar AI frameworks.

• Microservices and event-driven architectures.

• CI/CD, DevOps/MLOps, Infrastructure as Code (Terraform).

• Enterprise integrations with scalability, observability, and security considerations.

Good to Have
 

• AI Copilots or Agentic AI platforms.

• AI observability platforms.

• Prompt lifecycle management.

• Guardrails and Responsible AI.

• MCP (Model Context Protocol).

• Knowledge graphs.

• Semantic Search.

• Database internals.

• Linux internals.

• Performance engineering.

• AI Governance.

• Multi-tenancy.

• Service Level Objectives (SLOs).

• Enterprise workload modernization.

Self-Assessment Questions
 

• Have I built production-grade Generative AI or LLM applications?

• Have I designed distributed cloud-native systems running at enterprise scale?

• Am I comfortable architecting AI applications using RAG, AI Agents, and Vector Databases?

• Have I deployed AI models and production inference pipelines using Kubernetes or cloud platforms?

• Can I independently design scalable microservices while mentoring other engineers?

Career Level - IC4