Base Salary
$79k - $210k/yr
Responsibilities
- Design and implement authoritative and recursive DNS data-plane components for low-latency, high-throughput processing.
- Build and operate production services and libraries using Go, C, Java, or Python.
- Optimize CPU, memory, network I/O, event loops, concurrency, sockets, and performance through profiling and benchmarking.
- Own components end to end, including architecture, testing, safe rollout, observability, capacity planning, and operational health.
- Develop metrics, logs, traces, SLOs, dashboards, alerts, and on-call playbooks.
- Improve reliability through fault-tolerant design, graceful degradation, safe deployments, and proactive capacity planning.
- Collaborate with control plane, security, SRE, and operations teams on DNS platform improvements.
- Provide technical leadership through architecture reviews, code reviews, mentorship, and engineering-standard improvements.
- Drive production improvements across performance, reliability, security, and operational readiness.
Requirements
- At least five years of experience building, managing, or operating large-scale distributed infrastructure in SaaS, cloud, or hybrid-cloud environments.
- At least three years of hands-on experience with Linux operating systems.
- Strong experience building and operating production-grade distributed systems or network services.
- Proficiency in one or more of Go, C, Java, or Python, with willingness to work across languages.
- Understanding of Linux systems, networking fundamentals, TCP/UDP, sockets, concurrency, and performance profiling.
- Experience designing highly available systems and executing canary, progressive, and feature-flagged production rollouts.
- Deep DNS knowledge, including DNS RFCs, DNS over UDP/TCP, EDNS(0), DNSSEC, caching, zone transfers, rate limiting, and load balancing.
- Experience with high-performance patterns such as epoll/kqueue, asynchronous I/O, low-lock or lock-free data structures, and packet processing.
- Familiarity with DDoS mitigation, abuse prevention, and L4/L7 traffic engineering.
- Experience with containers and Kubernetes, including service meshes and network policies where relevant.
- Infrastructure-as-code experience, particularly with Terraform.
- Experience with unit, integration, fuzz, property-based, performance, and chaos testing.
- Experience operating mission-critical 24/7 services and using AI-assisted development tools while maintaining engineering judgment, code quality, ownership, and security standards.
Benefits
- Oracle provides medical, dental, vision, disability, life insurance, AD&D, flexible spending accounts, commuter and parking benefits, 401(k) matching, paid vacation, 11 paid holidays, paid sick leave, paid parental leave, adoption assistance, an employee stock purchase plan, financial planning, group legal services, and voluntary insurance benefits.
- The U.S. hiring range is $79,200 to $209,500 per year, with possible bonus and equity eligibility.
- The posting generally accepts applications for at least three calendar days or while the role remains posted.
About Oracle
Oracle is a global leader in AI, delivering the cloud infrastructure, data, and applications that organizations across the world trust to successfully achieve business outcomes at scale. Oracle Cloud Infrastructure (OCI) provides fast, flexible, scalable AI infrastructure. With superior compute performance and network design, a comprehensive choice of AI services for developing and orchestrating agentic AI workflows at scale, and unrivaled data control, security, privacy, and governance, OCI is designed for AI workloads. It also gives customers the flexibility to run their workloads wherever they need by supporting public cloud, multicloud, hybrid cloud, sovereign, and on-premises deployments. The Oracle AI Database is the only database with AI natively built in everywhere. By bringing AI to where data lives, the Oracle AI Database delivers enterprise-grade AI securely, cost-effectively, and at scale. In-database machine learning and vector search enable AI models to run where data resides. Support for multi-modal data (structured, unstructured, graph, vector) enables richer AI use cases. The Oracle AI Data Platform enables organizations to build, deploy, and govern AI agents and applications on top of private, secure, and distributed enterprise data. This enables organizations to operationalize AI without compromising data security or control. Oracle Applications embed AI directly into business workflows and industry processes to ensure AI is delivered in context, where work happens. They include the only applications suite that brings AI to every aspect of a business, with AI-powered ERP, HCM, and CX applications, and the Oracle Health Suite which provides applications for managing the entire healthcare ecosystem. Oracle also provides industry-specific cloud application suites for more than two dozen industries and NetSuite, the world’s first cloud computing company. This LinkedIn page serves as Oracle’s official global company page.