Oracle has 61 active AI-related job listings, with a significant focus on roles related to agents, which constitute 66% of the openings. The majority of these positions are within the Engineering function, and hiring is primarily concentrated in the United States. Frequently mentioned technical tags include agent_orchestration, llm_observability, and model_serving, suggesting a direction towards managing and deploying large language models. Over the last 30 days, Oracle has seen a substantial increase in AI hiring, with 55 new roles posted, representing a 267% rise compared to the preceding 30-day period.
Currently tracking 76 active AI roles, with 1131 new openings in the last 4 weeks. Primary focus: Agent · Engineering. Salary range $79k–$355k (avg $172k).
Oracle currently has 126 active AI-related roles in our index. The most common open titles are: Principal Software Engineer (7), Principal AI Agent / ML Software Engineer (OCI) (4), Principal Application Software Engineer (4), Senior Member of Technical Staff - US Citizenship Required (3), Software Developer 4 (3). Most positions are in Engineering and Product.
Oracle's active AI hiring is concentrated in: agents (48%), serving infrastructure (22%), application (20%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Oracle is hiring AI talent in: United States (104 roles), India (13 roles), Brazil (4 roles), Switzerland (1 role).
Job postings at Oracle most frequently mention: Cloud Infrastructure, Agentic Systems, Distributed Systems, Production ML Systems, Process Mining.
In the past 30 days, Oracle has posted 118 new AI-related roles. That is a +57% change versus the prior 30 days (75 → 118).
| Title | Stage | AI score |
|---|---|---|
| Principal Data Scientist This Principal Data Scientist role focuses on developing next-generation scalable, AI-driven platforms, specifically in Generative AI systems, LLMs, RAG, and AI Agent frameworks. The role involves deep understanding and practical experience with agent concepts like planning, tool use, memory management, and collaboration, aiming to integrate data and intelligence within enterprise architecture. | Agent | 8 |
