Oracle

Compensation

Full Description

We’re looking for experienced AI Developers (IC4/IC5 level) to join our team and help shape the future of AI at Oracle. In this role, you’ll lead the design and development of advanced AI applications, particularly those powered by large language models (LLMs), and help integrate them across Oracle’s Fusion ecosystem. You’ll work on cutting-edge problems, set engineering best practices, and collaborate with cross-functional teams to deliver secure, scalable, and responsible AI solutions. We encourage applicants from all backgrounds and experiences to apply — if you’re passionate about AI and meet most of the qualifications, we want to hear from you. What You’ll Do: LLM Application Engineering Architect and implement scalable applications using LLMs, focusing on prompt engineering, model customization, and performance optimization. Design and orchestrate agent-based solutions (e.g., using LangGraph or similar), including task decomposition, tool invocation, and setting up guardrails for safe operations. Develop effective RAG (retrieval-augmented generation) pipelines with robust chunking, embedding model selection, and vector store optimization. Structure and refine prompts, manage tool/function calling, and evaluate when to use general vs. fine-tuned models based on trade-offs like accuracy, latency, and cost. Build secure, scalable integrations with enterprise systems, using NL2SQL patterns and API connectivity. AI/ML Engineering Design, train, and optimize machine learning models for practical, real-world use cases. Build end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, and deployment. Work closely with data engineers and developers to embed ML into production systems. Monitor model performance and retrain as needed to maintain quality and relevance. LLMOps & Platform Engineering Manage versioning for prompts, models, and pipelines; run controlled experiments (A/B tests) and deployments. Implement observability for agent workflows, including tracing, logging, retries, and fallback mechanisms. Data Engineering & Feature Development Lead data acquisition, transformation, and feature engineering efforts to support reliable training and inference. Ensure clear schema definitions, metadata tracking, and lineage management. Evaluation, Quality, and Safety Define and maintain rigorous evaluation processes (e.g., precision/recall, hallucination detection, business alignment). Implement and enforce Responsible AI practices, including privacy protection, access controls, and secure data handling. Conversational UX & Fusion Integration Set standards for conversational UX, including multi-turn dialogues and natural language interfaces. Design AI components that integrate seamlessly into Oracle Fusion applications, promoting automation and user-centric workflows. Thought Leadership & Collaboration Mentor and support teammates; advocate for best practices in AI/ML development. Collaborate in agile pods and influence architectural and strategic decisions across teams. Evaluate emerging AI technologies and run proof-of-concept experiments to drive innovation