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.

Career Level - IC4

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

- Bachelors or Masters degree in Computer Science or related discipline.

- Solid 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

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Cloud Service Development Engineer (Bengaluru)
🏢 Oracle
📍 Bengaluru