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 +64% change versus the prior 30 days (72 → 118).
| Title | Stage | AI score |
|---|---|---|
| Software Developer 4 Software Developer 4 role at Oracle focused on building advanced AI applications for network automation, optimization, and security. Responsibilities include designing and implementing AI/ML systems for serving and training models, incorporating research on AI agents and inference, optimizing training and inference workloads, leading initiatives in RAG and LLM fine-tuning, and developing GPU-accelerated AI pipelines. Requires strong Python, ML frameworks, distributed systems, and MLOps experience. | ServePost-train | 8 |
| Principal Machine Learning Engineer This Principal Machine Learning Engineer role at Oracle Cloud Infrastructure (OCI) focuses on building state-of-the-art training infrastructure for massive GPU clusters and designing agentic systems for enterprise-scale deployment. The role involves the entire software and model development lifecycle, including training, fine-tuning, model serving, and evaluation, with a strong emphasis on distributed systems, cloud architecture, and scaling heterogeneous CPU/GPU training infrastructure for large multimodal frontier models. |
| ServePost-train |
| 8 |
| GPU/CPU Systems Engineer This role focuses on the engineering and development of AI hardware platforms, specifically GPU/CPU systems, within Oracle's Cloud Infrastructure. The engineer will be involved in platform definition, development oversight, system integration, performance testing, and characterization, working closely with internal teams and external suppliers to scale and optimize Oracle's AI Cloud solutions. The role emphasizes hardware and system engineering expertise for next-generation AI platforms. | Serve | 7 |
| [REMOTE] Principal Platform Software Engineer- Oracle Clinical Digital Assistant This role focuses on leading the design and implementation of the AI-Assist platform, which involves backend infrastructure for data ingestion, processing, and retrieval, as well as integrating search and NLP capabilities. It requires strong software engineering fundamentals, cloud-native development experience, and knowledge of data architecture and Oracle Database. The role also involves ensuring data security and privacy within healthcare regulations and mentoring junior engineers. | ServeAgent | 7 |
| Software Developer 3 Software Developer 3 role focused on scaling and optimizing AI infrastructure components, specifically GPU control and data planes, for large-scale AI clusters. The role involves designing and developing distributed systems, providing technical leadership, and ensuring reliability and performance for customer AI workloads. | Serve | 7 |
| Software Developer 3 Software Developer 3 role focused on scaling and optimizing AI infrastructure components, specifically GPU control and data planes, for large-scale AI clusters. The role involves designing and developing distributed systems, providing technical leadership, and ensuring reliability and performance for customer AI workloads. | Serve | 7 |
| Senior AI Site Reliability Developer 3 This role focuses on building and operating the infrastructure for an AI-first Electronic Health Record platform. The Senior AI Site Reliability Developer will design, build, and operate reliable, scalable infrastructure and data pipelines, with a strong emphasis on advancing automation, observability, and AI-assisted reliability practices. This includes exploring and applying Generative AI and agentic AI for incident response, system resilience, and operational efficiency, as well as managing cloud environments and data technologies. | ServeAgent | 7 |
| Principal Engineer - AI Networking Principal Engineer focused on designing, implementing, and optimizing RDMA-based networking infrastructure critical for large-scale AI training and inference workloads. This role involves deep systems programming, high-performance networking, and distributed communication systems to enhance the performance and scalability of AI infrastructure. | Serve | 7 |
| Senior Principal Engineer - AI Networking Senior Principal Engineer role focused on AI networking infrastructure, specifically RDMA and distributed communication systems for large-scale GPU clusters supporting AI training and inference. The role involves architecture, design, implementation, and performance optimization of software components. | Serve | 7 |
| Senior Principal Engineer - AI Networking Senior Principal Engineer role focused on AI networking infrastructure, specifically RDMA and distributed communication systems for large-scale GPU clusters supporting AI training and inference. The role involves architecture, design, implementation, and performance optimization of software components. | Serve | 7 |
| Software Development Snr Manager Senior Manager to lead a team designing, developing, and optimizing AI compute infrastructure components, focusing on GPU control and data planes to enhance customer workload performance and experience on Oracle's AI infrastructure. The role involves people management, setting team goals, driving modern software engineering practices, and ensuring solutions are secure, reliable, and monitored. | Serve | 7 |
| Software Developer 4 Software Developer to build foundational data systems for AI-native enterprise intelligence, focusing on evolving Oracle Database to support semantic retrieval, hybrid query execution, and AI-powered retrieval capabilities close to the data. This involves designing and building high-performance AI-powered retrieval primitives within the database kernel, developing scalable indexing algorithms, engineering hybrid retrieval capabilities, and building database-native support for advanced query features and AI retrieval for lakehouse environments. | ServeAgent | 7 |
| Sr Principal TPM (IC5) – AI Infrastructure This role leads strategic, large-scale programs for AI infrastructure, focusing on GPU deliveries, capacity planning, and new product introductions. The TPM will define and drive execution frameworks, manage risks, and mentor other TPMs to ensure the scaling of AI infrastructure delivery and operations. | Serve | 7 |
| Senior Principal Network Development Engineer (IC5) – Backend NIC Qualification & NPI (OCI AI2 – Performance & NIC Engineering) Senior Principal Network Development Engineer focused on backend NIC qualification and NPI for AI superclusters. The role requires deep expertise in NIC architecture, distributed systems networking for AI/ML, and performance tuning to ensure RDMA performance, cluster scale, and workload isolation. Responsibilities include leading qualification strategies, defining validation methodologies, driving performance characterization, collaborating with vendors and internal teams, building automated validation frameworks, and establishing qualification gates for AI infrastructure. | Serve | 7 |
