The Oracle Cloud Infrastructure (OCI) Security and Compliance Platform Engineering organization offers a unique opportunity to help build the next generation of AI-driven cybersecurity solutions at cloud scale. Our mission is to protect OCI, Oracle, and our global customers by developing intelligent, autonomous security systems capable of detecting, investigating, and mitigating evolving cyber threats in real time.

As part of this team, you will work on highly scalable, low-latency distributed systems that ingest and process massive volumes of telemetry, security events, and operational data across OCI. We leverage cutting-edge technologies including Generative AI (GenAI), Large Language Models (LLMs), Machine Learning (ML), and advanced analytics to build adaptive security platforms that continuously improve their ability to identify and respond to threats.

This role provides the opportunity to design and develop large-scale data pipelines, distributed databases, cloud-native services, and AI-powered security capabilities that operate at one of the world's largest cloud infrastructures. You will collaborate with engineers, architects, data scientists, and security experts to solve complex technical challenges while delivering innovative solutions that directly impact the security posture of Oracle Cloud.

If you are passionate about building high-scale distributed systems, working with big data and AI technologies, and shaping the future of cloud security, we invite you to join us in redefining cybersecurity for the cloud era.

Responsibilities

Lead the end-to-end design, development, testing, deployment, and operational excellence of highly scalable, secure, and multi-tenant cloud services and platforms.
Architect and build cloud-native applications, distributed systems, big data platforms, and data processing pipelines that support high-volume, low-latency workloads.
Design, develop, and deploy AI-powered solutions, including AI agents, MCP (Model Context Protocol) integrations, LLM-based applications, and intelligent automation capabilities.
Drive technical architecture and design decisions to ensure high availability, reliability, scalability, security, observability, and operational efficiency across cloud and AI workloads.
Collaborate closely with engineering leaders, architects, product managers, program managers, and cross-functional teams to define requirements and deliver high-quality product features on schedule.
Partner with internal and external application teams to enable seamless integrations, provide technical guidance, and drive successful adoption of platform capabilities.
Proactively identify, assess, and mitigate technical risks, operational issues, and execution challenges to ensure successful project delivery.
Continuously evaluate and leverage emerging cloud technologies, AI innovations, and engineering best practices to improve platform capabilities and development processes.
Mentor and guide engineers through technical leadership, design reviews, code reviews, and engineering best practices to elevate overall team effectiveness.

Must-Have Skills

BS/MS in Computer Science, Engineering, or a related technical field (or equivalent practical experience) with 5+ years of software engineering experience.
Strong experience designing and building cloud-native applications, microservices, and distributed systems in large-scale production environments.
Minimum 3+ years of hands-on experience architecting, deploying, and operating cloud infrastructure on public cloud platforms such as OCI, AWS, Azure, or GCP.
Hands-on experience building AI-powered applications, AI agents, MCP (Model Context Protocol) integrations, LLM-based solutions, and intelligent automation workflows.
Strong experience with big data technologies, large-scale data processing systems, ETL pipelines, or distributed data platforms.
Proficiency in one or more modern programming languages such as Java, Kotlin, Python, or C#, with strong software design and development fundamentals.
Strong understanding of operating systems, networking, distributed systems, fault-tolerant architectures, high-availability systems, and scalable system design.
Experience with containerization and orchestration technologies such as Docker and Kubernetes.
Proven ability to troubleshoot complex technical challenges, make sound architectural decisions, and drive solutions independently in fast-paced environments.
Excellent communication, collaboration, and stakeholder management skills, with the ability to clearly articulate technical concepts to diverse audiences.
Strong ownership mindset, attention to detail, problem-solving ability, and demonstrated adaptability to learn and apply new technologies quickly.

Preferred / Nice-to-Have Skills

Experience designing and implementing high-availability, disaster recovery, performance optimization, and security architectures for cloud-native systems.
Experience with cloud observability and monitoring platforms such as Prometheus, Grafana, OpenTelemetry, or similar technologies.
Hands-on experience building and maintaining CI/CD pipelines using tools such as Jenkins, GitLab CI/CD, GitHub Actions, or similar.
Familiarity with build and dependency management tools such as Maven, Gradle, Ant, or equivalent ecosystems.
Experience working with large-scale enterprise platforms, multi-tenant SaaS architectures, and platform engineering practices.
Exposure to MLOps, model deployment, AI infrastructure, vector databases, RAG architectures, and production AI lifecycle management.

Duties and tasks are varied and complex needing independent judgment. Fully competent in own area of expertise. May have project lead role and or supervise lower level personnel. BS or MS degree or equivalent experience relevant to functional area. 4 years of software engineering or related experience.

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