Join Oracle Cloud Infrastructure (OCI) and contribute to building the future of enterprise cloud. As a core member of the Compute organization, you'll be instrumental in powering our cloud services, including VMs, BMs, and GPUs. This is an opportunity to work on the foundational elements of cloud technology and create magical experiences for our customers.

We are seeking passionate, hands-on engineers with a flair for solving complex challenges in large-scale distributed systems, virtualised cloud environments, and highly available services. You will drive innovation by developing automation that diagnoses infrastructure issues, orchestrates recovery, and minimizes manual operational tasks across our extensive compute fleet. Expertise in Java, Python, Terraform, CI/CD, Linux, networking, microservices, and system engineering is essential. We value simplicity, scale, collaboration, and a continuous learning mindset.

Take ownership of critical services and technology areas, driving their development and evolution as a senior software developer. Gain a comprehensive understanding of end-to-end system architecture, call flows, configurations, dependencies, and overall service behavior in production environments. You will be responsible for the design, development, and maintenance of our mission-critical stack, prioritizing security, resilience, scalability, and performance. Your role will involve defining and implementing improvements to service architecture and articulating the technical characteristics of various services and technology domains. You will engineer advanced capabilities for the Oracle Cloud service portfolio and clearly communicate the scale, capacity, security, and performance requirements of the services and technology stack.

Demonstrate a strong grasp of automation and orchestration principles, designing and developing reusable diagnostic and remediation workflows. Translate operational runbooks into robust, testable automation solutions. Integrate seamlessly with monitoring, incident management, and infrastructure services to facilitate end-to-end issue resolution. Implement safeguards within automated actions, including validation, retries, recovery, and escalation mechanisms.

Act as the primary escalation point for complex or critical issues, leveraging deep service and dependency knowledge to troubleshoot and define mitigations. Analyze production telemetry and incident patterns to identify automation opportunities, measuring improvements in resolution times, reliability, and operational efficiency. Clearly explain the impact of architectural decisions on distributed systems. Cultivate professional curiosity and a commitment to developing profound expertise in services and technologies.

Qualifications include a Bachelors/Masters in Computer Science and Engineering or a related engineering field, with over 3 years of experience in developing and operating large-scale, highly available distributed systems. Strong experience building ML or LLM-based systems using Python, Java, PyTorch, TensorFlow, or modern LLM frameworks is required. Hands-on experience with tools like Claude Code, Codex, or Github Copilot, along with a deep understanding of observability data (logs, metrics, traces) and platforms (Datadog, Splunk, Prometheus, Grafana, ELK), is crucial. Experience designing and deploying RAG pipelines, embeddings, intent models, or operational chatbots is a plus. Familiarity with system design, platform & reliability engineering, ML engineering, data engineering, or AIOps-oriented roles, alongside strong experience architecting streaming or event-driven systems (Kafka, Kinesis, Pub/Sub), is expected. Proficiency with cloud-native systems, Kubernetes, microservices, and modern deployment patterns is essential. Excellent problem-solving, critical thinking, and communication skills are vital for collaborating effectively across SRE, platform, service management, and engineering teams.