Senior Core Infrastructure Engineer

Oracle•Santa Clara, CA

About The Position

Join Oracle Cloud Infrastructure's (OCI) Object Storage Metadata Service (MDS) team to design, develop, and operate distributed metadata infrastructure that powers OCI Object Storage at cloud scale. The role addresses metadata consistency, scalability, performance, fault tolerance, and high availability, and calls for hands-on systems programming, end-to-end ownership, and an AI-first approach to engineering productivity. The engineer will build and improve foundational metadata infrastructure, strengthen the scalability and operational efficiency of distributed storage services, and deliver production-ready infrastructure capabilities. The role also contributes to engineering quality through technical leadership, mentorship, automation, and continuous improvement. The position involves production operations, including monitoring, troubleshooting, incident response, root cause analysis, and on-call rotations. It also includes collaboration with engineers, architects, and partner teams on design and code reviews, documentation, and knowledge sharing.

Requirements

The posting's qualifications section lists 3–5+ years of software development experience, including building and operating production systems or large-scale distributed services.
The minimum qualifications list one of the following: 8 years of software development experience; a relevant bachelor's or B.Tech degree and 4 years of software development experience; a relevant master's or M.Tech degree and 2 years of software development experience; or a doctorate in a listed or related field.
Proficiency in C++, Java, Go, or Rust, with solid foundations in data structures, algorithms, software design, and performance optimization.
Deep expertise in distributed systems design, including scalability, resiliency, concurrency, fault tolerance, service communication, and API design.
Experience with cloud-native technologies, including containers, Kubernetes, CI/CD pipelines, Infrastructure-as-Code, and automated testing frameworks.
Experience building observability solutions using metrics, distributed tracing, centralized logging, dashboards, and alerting systems.
Familiarity with AI-assisted development tools and a proactive approach to AI-first engineering practices.
Strong problem-solving, communication, collaboration, and ownership skills.
Demonstrated ability or knowledge in distributed systems, prototyping, computer science programming, software engineering, web development, innovation, cross-functional collaboration, information vulnerability assessment and mitigation, operating systems, API development and integration, applied algorithm engineering, and source control.
At least 2 years of professional experience with cloud platforms.
At least 3 years of experience working in system-level testing and automation.
At least 2 years of experience delivering and operating large-scale distributed systems.

Nice To Haves

Experience building or operating distributed storage systems, object storage, metadata services, or distributed databases.
Knowledge of distributed metadata management, partitioning, replication, consistency models, and recovery mechanisms.
Experience optimizing cloud-scale services for latency, throughput, scalability, and availability.
Experience operating globally distributed services across multiple regions and availability domains.
Familiarity with OCI or other cloud infrastructure platforms, containers, and deployment automation.
Experience developing AI-powered automation for software engineering, testing, debugging, or production operations.
The preferred qualifications also list the education and software-development experience alternatives described in the minimum qualifications.
The preferred qualifications list 2 years of experience with cloud platforms under People Leadership / Management Experience.

Responsibilities

Design, develop, and optimize high-performance distributed metadata services, focusing on scalability, consistency, resiliency, and low latency.
Build resilient infrastructure using replication, redundancy, failure recovery, and automated failover mechanisms.
Lead automation initiatives across the software development lifecycle, including CI/CD, testing frameworks, deployment automation, and Infrastructure-as-Code.
Support production services through monitoring, troubleshooting, incident response, root cause analysis, and on-call rotations.
Drive reliability, scalability, and operational readiness through capacity planning, incident response, root cause analysis, and continuous improvement.
Use AI tools for coding, debugging, testing, code reviews, incident analysis, and workflow automation.
Own features end-to-end; participate in design and code reviews; maintain technical documentation and runbooks; and collaborate to deliver reliable cloud infrastructure.
Mentor engineers, influence technical strategy, and raise engineering standards through design reviews and technical leadership.
Improve the scalability, performance, reliability, and operational efficiency of distributed storage services.
Accelerate engineering productivity through AI-assisted development, automation, and continuous improvement.