Senior Platform Software Engineer

Oracle•Nashville, TN

About The Position

Oracle Cloud Infrastructure (OCI) builds enterprise cloud services with a startup-like pace and a focus on customer needs. The Generative AI Code Assist Service team works at the intersection of artificial intelligence and cloud infrastructure. Oracle Agent Platform is a managed platform for building, deploying, governing, and operating AI agents at enterprise scale across OCI. The team builds and operates cloud services using generative AI technologies to address challenging customer problems. The Senior Platform Software Engineer owns software architecture and development for the Oracle Generative AI Agent Platform Service. The role owns moderately complex platform components, such as a service module or SDK area, and evolves their contracts for multi-tenant use. It involves hands-on coding and distributed-systems work, deep debugging across a bounded set of services, and targeted resilience and capacity improvements. The engineer analyzes platform usage, performance, and error budgets, and creates team-scoped documentation, samples, and adoption guidance. The engineer designs, tests, optimizes, and maintains software aligned with established architecture; leads code reviews in designated areas; and applies testing, observability, secure coding, and operational practices. The role also works across teams to address customer issues, improve products based on feedback, and support reliable, highly available cloud-scale services. Senior engineers work independently, provide technical leadership, and balance delivery speed with quality through iterative improvements.

Requirements

At least 4 years of application development experience.
Proficiency in Java and one other major programming or scripting language, such as Python or Go.
Strong background in AI/ML, with a focus on generative AI and AI-driven code generation.
Strong distributed systems fundamentals.
Bachelor’s degree in computer science, engineering, or a related engineering field.
Strong troubleshooting skills and demonstrated ability to deliver quality code.
Experience with container orchestration technologies such as Kubernetes.

Nice To Haves

Terraform knowledge.
At least 4 years of experience with public cloud tools or services such as AWS, Azure, or GCP.
Master’s degree in computer science.
Experience with generative AI technologies.

Responsibilities

Own and evolve a bounded platform component, such as a service module or SDK area, including contracts for multi-tenant use.
Debug issues across a limited service graph and drive compatibility-safe remediation plans.
Implement targeted resilience and capacity improvements and document adoption guidance for team consumers.
Design software solutions and identify requirements to achieve business and operational goals.
Develop software features and enhancements, clarify designs and code through documentation, and improve the software development lifecycle.
Lead code reviews in designated areas and troubleshoot and fix moderately complex software issues.
Implement functional and non-functional testing, quality assurance, error logging, monitoring, and observability.
Profile and optimize performance and resolve moderately complex API functionality and integration issues.
Implement API versioning, lifecycle, and interoperability strategies.
Design and develop software aligned with established system architecture, including performance and scalability strategies.
Collaborate across teams to understand customer issues, provide technical guidance, and develop solutions and product enhancements.
Support customer issue and defect handling, including investigation of complex maintenance issues and agreement on short- and long-term solutions.
Follow and improve development practices and coding standards; apply industry best practices and secure coding practices.
Perform maintenance and testing for system upgrades and patches, and improve automation, testing, debugging, availability, health, support, and reliability.
Independently manage work, timelines, deliverables, and priorities, adapting to resource or timeline changes.
Collaborate across teams and build understanding of business, stakeholder, and customer needs.
Identify and troubleshoot standard and non-standard issues, escalate more complex issues as appropriate, and contribute to knowledge sharing.
Continuously build skills and knowledge, seek feedback and training, and contribute to team learning.
Recommend process, protocol, and workflow improvements to increase team efficiency and effectiveness.