Senior AI Native Platform Engineer (Java & Python)

JD: AI-Native Platform Engineer (IC3) – Oracle Health Infrastructure and Platform Services About the Company/Team Oracle Health Infrastructure and Platform Services builds and operates the cloud foundations, shared platforms, and engineering capabilities that support Oracle Health products and services. The Oracle Cloud Infrastructure (OCI) team provides the opportunity to build and operate massive-scale, integrated cloud services in a broadly distributed, multi-tenant environment. OCI is committed to delivering secure, reliable cloud products for customers addressing some of the world’s most important challenges. Within Oracle Health, this team is building an AI-native engineering platform: a set of intelligent agents and reusable cloud capabilities that help engineering teams understand complex systems, reason through problems, and safely execute work across the software lifecycle. Job Summary Oracle Health Infrastructure and Platform Services is looking for engineers with experience building cloud-native, AI-assisted platforms and systems. The role combines hands-on software engineering, cloud platform development, and operational ownership. You will help turn complex or manual engineering work into safe, repeatable platform capabilities and runbooks that improve developer productivity, reliability, and customer outcomes. The ideal candidate brings strong engineering fundamentals, sound judgment in mission-critical or regulated environments, and curiosity about applying emerging AI technologies responsibly in production systems. Key Responsibilities Design, build, test, deploy, and operate AI-native platform services that improve how Oracle Health engineers build, deliver, and manage software. Build intelligent agents and AI-powered capabilities that augment engineering teams, accelerate software development, and help engineers solve complex problems with greater speed and confidence. Contribute to the design and implementation of scalable platform capabilities, partnering with senior engineers to solve complex technical problems. Collaborate with engineering, product, and domain teams to understand requirements and deliver high-quality software with measurable impact. Develop cloud-native distributed systems with a focus on scalability, reliability, security, maintainability, observability, and developer experience. Experiment with emerging AI technologies, validate ideas through prototypes, and help evolve successful concepts into production-ready capabilities. Build reusable software components, APIs, tools, and platform services that can be adopted across multiple engineering teams. Contribute to engineering excellence through code reviews, design discussions, automated testing, operational readiness, documentation, and continuous learning. At least 5 years of software engineering experience building scalable applications, backend services, developer platforms, or distributed systems. Bachelor’s degree in Computer Science or a related technical discipline, or equivalent practical experience. Demonstrated ability to solve technical problems, deliver high-quality software, and collaborate effectively within engineering teams. Strong programming skills in Java, Python, or another object-oriented programming language. Strong computer science fundamentals, including data structures, algorithms, operating systems, networking, and distributed systems. Experience developing cloud-native applications or services on OCI, AWS, Azure, Google Cloud Platform, or a comparable cloud environment. Experience with modern software engineering practices, including source control, automated testing, code review, CI/CD, and production support. Understanding of scalability, reliability, security, observability, and maintainability in distributed systems. Ability to troubleshoot software and platform issues using logs, metrics, traces, and other diagnostic data. Strong written and verbal communication skills. Hands-on, learning-oriented mindset with a focus on delivering reliable outcomes. Strong analytical, troubleshooting, and problem-solving skills. Ability to work effectively with globally distributed engineering, product, operations, security, and domain teams. Ability to balance speed, quality, and operational safety in a mission-critical environment. Commitment to clear technical documentation, maintainable code, and continuous improvement. Experience building AI-enabled applications, intelligent agents, or software using modern AI development tools. Experience with AI engineering concepts such as retrieval-augmented generation (RAG), tool calling, Model Context Protocol (MCP), vector databases, prompt evaluation, or model orchestration. Experience using Python for AI, automation, tooling, or backend development. Experience with Kubernetes, Docker, Terraform, Infrastructure as Code, or cloud-native platform engineering practices. Experience building developer tools, internal platforms, or engineering productivity solutions. Experience with observability, telemetry, logging, tracing, diagnostics, or production engineering. Experience working on large-scale distributed systems or in healthcare, security, compliance, or another mission-critical enterprise environment. Qualifications & Skills Mandatory Qualifications Experience At least 5 years of software engineering experience building scalable applications, backend services, developer platforms, or distributed systems. Bachelor’s degree in Computer Science or a related technical discipline, or equivalent practical experience. Demonstrated ability to solve technical problems, deliver high-quality software, and collaborate effectively within engineering teams. Technical Skills Strong programming skills in Java, Python, or another object-oriented programming language. Strong computer science fundamentals, including data structures, algorithms, operating systems, networking, and distributed systems. Experience developing cloud-native applications or services on OCI, AWS, Azure, Google Cloud Platform, or a comparable cloud environment. Experience with modern software engineering practices, including source control, automated testing, code review, CI/CD, and production support. Understanding of scalability, reliability, security, observability, and maintainability in distributed systems. Ability to troubleshoot software and platform issues using logs, metrics, traces, and other diagnostic data. Strong written and verbal communication skills. Core Competencies Hands-on, learning-oriented mindset with a focus on delivering reliable outcomes. Strong analytical, troubleshooting, and problem-solving skills. Ability to work effectively with globally distributed engineering, product, operations, security, and domain teams. Ability to balance speed, quality, and operational safety in a mission-critical environment. Commitment to clear technical documentation, maintainable code, and continuous improvement. Good-to-Have Qualifications Experience building AI-enabled applications, intelligent agents, or software using modern AI development tools. Experience with AI engineering concepts such as retrieval-augmented generation (RAG), tool calling, Model Context Protocol (MCP), vector databases, prompt evaluation, or model orchestration. Experience using Python for AI, automation, tooling, or backend development. Experience with Kubernetes, Docker, Terraform, Infrastructure as Code, or cloud-native platform engineering practices. Experience building developer tools, internal platforms, or engineering productivity solutions. Experience with observability, telemetry, logging, tracing, diagnostics, or production engineering. Experience working on large-scale distributed systems or in healthcare, security, compliance, or another mission-critical enterprise environment. Self-Assessment Questions Before applying, consider the following questions to assess your fit for the role: Have I built and operated production software or cloud services using Java, Python, or another object-oriented programming language? Can I explain how I have applied distributed-systems fundamentals to improve scalability, reliability, security, or maintainability? Have I contributed to reusable developer tools, platform services, automation, or AI-enabled capabilities used by other engineers? Can I demonstrate effective collaboration, testing, troubleshooting, documentation, and operational ownership for software delivered to production? Qualifications & Skills Mandatory Qualifications Experience At least 8 years of software engineering experience building scalable applications, backend services, developer platforms, or distributed systems. Bachelor’s degree in Computer Science or a related technical discipline, or equivalent practical experience. Demonstrated ability to independently own complex engineering problems from discovery through production and measurable adoption. Strong programming skills in Java, Python, or another object-oriented programming language. Deep understanding of distributed systems, cloud-native architectures, API design, software engineering best practices, and production operations. Experience designing reusable platform capabilities, developer tools, or engineering solutions adopted by multiple teams. Demonstrated ability to make sound architectural trade-offs across scalability, reliability, security, cost, maintainability, and developer experience. Experience leading technical design, resolving ambiguity, and driving complex initiatives across organizational boundaries. Ability to use operational data, customer feedback, and engineering metrics to prioritize work and demonstrate impact. Strong communication, technical leadership, mentoring, and problem-solving skills. Platform-first mindset with a focus on leverage, reuse, and durable engineering outcomes. Strong product and customer judgment when identifying high-value engineering problems. Ability to lead through influence and collaborate effectively with globally distributed engineering, product, operations, security, and domain teams. Sound judgment when introducing new technology into mission-critical or regulated environments. Ability to raise engineering standards through clear architecture, documentation, mentoring, and operational accountability. Experience building AI-native applications, intelligent agents, or agentic systems using large language models. Experience with AI engineering concepts such as retrieval-augmented generation (RAG), tool calling, Model Context Protocol (MCP), vector databases, evaluation frameworks, guardrails, or model orchestration. Experience applying AI to software engineering, developer productivity, incident response, diagnostics, or platform operations. Experience building cloud-native platforms on OCI, AWS, Azure, Google Cloud Platform, or a comparable cloud environment. Experience with Kubernetes, Docker, Terraform, Infrastructure as Code, and modern platform engineering practices. Experience designing reusable platform capabilities adopted across multiple engineering organizations. Experience with observability platforms, telemetry pipelines, diagnostics, production engineering, healthcare, security, compliance, or another highly regulated environment. Technical Skills Core Competencies Good-to-Have Qualifications Self-Assessment Questions Before applying, consider the following questions to assess your fit for the role: Have I independently discovered and owned an ambiguous, high-impact engineering problem from initial framing through production adoption? Have I designed reusable platform capabilities or developer tools that were adopted across multiple engineering teams? Can I demonstrate architectural leadership and sound trade-off decisions for scalable, reliable, secure distributed systems? Have I influenced technical direction, mentored engineers, and delivered measurable outcomes through cross-team collaboration? Career Level - IC4 Oracle Health Infrastructure and Platform Services is looking for engineers with experience building cloud-native, AI-assisted platforms and systems. The role combines hands-on software engineering, cloud platform development, and operational ownership. You will help turn complex or manual engineering work into safe, repeatable platform capabilities and runbooks that improve developer productivity, reliability, and customer outcomes. The ideal candidate brings strong engineering fundamentals, sound judgment in mission-critical or regulated environments, and curiosity about applying emerging AI technologies responsibly in production systems.