Base Salary
$93k - $210k/yr
Responsibilities
- Design, build, deploy, and operate highly available platform services for developer productivity and AI-assisted engineering workflows.
- Lead architecture and delivery of scalable systems that analyze service behavior, model traffic, generate workloads, and evaluate results.
- Develop agent-assisted canary, functional, integration, load, and performance testing workflows within safety controls.
- Apply machine learning and LLM capabilities to telemetry, API changes, incidents, test results, and engineering knowledge.
- Build traffic-generation and workload-modeling systems that reflect production usage, dependencies, and changing traffic patterns.
- Develop diagnostics for correctness, latency, error rates, reliability, scalability, and regression detection.
- Provide actionable explanations of failures and automate conversion of incidents and regressions into reusable test coverage.
- Design APIs, data pipelines, and integrations for OCI engineering teams while establishing reliability, observability, security, privacy, performance, and responsible-AI practices.
- Mentor engineers, lead cross-team technical initiatives, and influence technical direction.
Requirements
- Bachelor’s or master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- At least four years of professional software engineering experience building and operating production systems.
- Proficiency in one or more of Java, Go, Python, or C++.
- Strong knowledge of system design, algorithms, data structures, concurrency, APIs, and scalable architectures.
- Experience with backend services, distributed systems, microservices, event-driven applications, or large-scale data pipelines.
- Experience developing and operating cloud software using containerization and cloud-native architectures.
- Experience with service testing, reliability, observability, performance engineering, or production operations.
- Ability to troubleshoot complex systems using logs, metrics, traces, telemetry, and production data.
- Ability to lead technical initiatives across teams, communicate architectural decisions, and deliver production software.
- Preferred: experience with developer platforms, CI/CD systems, testing frameworks, machine learning, generative AI, LLMs, AI agents, retrieval-augmented generation, prompt engineering, or LLM evaluation.
- Preferred: experience with PyTorch, TensorFlow, Hugging Face Transformers, traffic replay, workload modeling, canary analysis, load testing, performance testing, chaos engineering, Kubernetes, containers, service meshes, or OCI and other public clouds.
- Preferred: experience analyzing API schemas, code changes, service dependencies, incidents, production traffic, mentoring engineers, and influencing architecture.
Benefits
- Medical, dental, and vision insurance; disability and life insurance; supplemental life insurance; flexible spending accounts; commuter and parking benefits; 401(k) with company match; paid vacation, 11 paid holidays, and paid sick leave.
- Paid parental leave, adoption assistance, employee stock purchase plan, financial planning, group legal services, and voluntary auto, homeowner, and pet insurance.
- The position is a U.S.-based salaried role with applications generally accepted for at least three calendar days or while the posting remains active.
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.