Oracle is looking to shape the future of AI by developing advanced AI applications, particularly those powered by large language models (LLMs), and integrating them across Oracle's Fusion ecosystem. The goal is to deliver secure, scalable, and responsible AI solutions to tackle cutting-edge problems and set engineering best practices.
Requirements
- Proficiency in Python (and/or Java), cloud-based data pipelines, and MLOps tools (e.g., OCI Data Science, MLflow, Kubeflow).
- Hands-on experience with models such as OpenAI, Anthropic, or open-source LLMs; familiarity with prompt engineering, fine-tuning, and deployment strategies.
- Experience integrating AI into enterprise cloud ecosystems.
- Deep understanding of NLP, conversational systems, and dialog design.
- Proven ability to design AI systems with safety, fairness, and governance in mind.
- Experience: 10+ years in software/AI development, with 3+ years focused on LLMs or related deep learning systems.
- Manage versioning for prompts, models, and pipelines; run controlled experiments (A/B tests) and deployments.
Responsibilities
- 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.
- 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.
Other
- Collaborate with cross-functional teams to deliver secure, scalable, and responsible AI solutions.
- 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.
- Excellent communication and mentorship skills; thrives in cross-functional, diverse teams.
