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Oracle is seeking a Principal Data Systems Software Engineer to design, architect, and build the next generation of cloud-native platform services powering Oracle Database Cloud. This is primarily a core software engineering role focused on large-scale distributed systems, cloud-native architecture, and enterprise platform development. The ideal candidate has extensive experience designing and building highly scalable backend systems, microservices, and cloud platforms, along with hands-on experience applying modern AI technologies such as Generative AI, LLMs, AI Agents, and Retrieval-Augmented Generation (RAG) to solve real-world engineering problems. You will work on critical platform capabilities including database provisioning, lifecycle management, monitoring, automation, and operational intelligence while helping evolve the platform with AI-powered capabilities that improve automation, reliability, and developer productivity. Key Responsibilities - Design, architect, and develop highly scalable cloud-native services supporting Oracle Database on OCI. - Build enterprise-grade distributed systems emphasizing scalability, resiliency, high availability, observability, and security. - Design and implement microservices and event-driven architectures for mission-critical cloud platform services. - Drive architecture and technical design for large-scale backend platform components. - Build platform capabilities for provisioning, lifecycle management, monitoring, automation, and operational workflows. - Apply Generative AI technologiesincluding LLMs, AI Agents, and RAGto enhance platform intelligence and operational automation. - Design enterprise integrations across databases, APIs, cloud services, and internal platforms. - Collaborate closely with Product Management, Compute Engineering, Operations, and other Oracle engineering teams. - Lead technical initiatives, mentor engineers, and influence engineering best practices. Troubleshoot complex production issues and drive root cause analysis for highly available cloud services. Qualifications & Skills Required - Bachelor's or Master's degree in Computer Science or related field. - 6+ years of experience designing and developing enterprise software products or cloud platform services. - Strong experience building large-scale distributed systems and cloud-native applications. - Proven experience designing and implementing backend services, microservices, and event-driven architectures. - Strong software engineering fundamentals including: - Distributed systems - Concurrency - System design - API design - Data modeling - Performance optimization - Strong programming experience in Java and/or Python . - Experience developing production services on OCI, AWS, Azure, or GCP. - Experience with Kubernetes, Containers, REST APIs, and cloud-native technologies. - Experience building enterprise software with scalability, availability, observability, and security as core design principles. - Experience with CI/CD pipelines, Infrastructure as Code (Terraform), and DevOps practices. - Experience integrating enterprise systems, databases, and cloud services. AI Experience Hands-on experience applying up-to-date AI technologies in production systems, including one or more of the following: - Generative AI applications - Large Language Models (LLMs) - Retrieval-Augmented Generation (RAG) - AI Agents - Prompt Engineering - Model orchestration frameworks - Vector databases and embeddings - AI evaluation frameworks - AI inference services Note: AI/ML expertise is expected as part of building modern intelligent cloud services. However, this role is fundamentally a software engineering and distributed systems position rather than an AI research or data science role. Preferred Qualifications Experience with one or more of: - Database platforms or database internals - Enterprise cloud platform development - AI Copilots or Agentic AI platforms - MCP (Model Context Protocol) - Knowledge Graphs - Semantic Search - Linux internals - Performance engineering - Multi-tenancy - SLO-driven service engineering - AI governance and responsible AI Enterprise workload modernization What We're Looking For We are looking for engineers who have: - Built enterprise software products used at large scale. - Designed and developed distributed systems running in production. - Strong backend development expertise in Java and/or Python. - Experience architecting cloud-native services and microservices. - A passion for applying AI technologies to improve enterprise platforms rather than building standalone AI products. Excellent system design and technical leadership skills. Self-Assessment You may be a great fit if you can answer \"Yes\" to most of these: - Have I designed and built large-scale enterprise software or cloud platform services - Have I architected distributed systems that run reliably at production scale - Am I experienced in Java and/or Python backend
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.