Senior Application Software Engineer

Oracle is building secure, scalable AI platform capabilities through Oracle Cloud Infrastructure (OCI), and this Senior Application Software Engineer role sits at the center of that effort. You will help shape AI control plane and data plane services, integrations, backend APIs, and reusable AI workflows that support enterprise employee productivity across Oracle.

What you’ll do

• Design, develop, deliver, and maintain secure and scalable AI software that improves employee productivity across Oracle.
• Build AI control plane and data plane services, including Codex integrations, memory capabilities, and model routing, aligned with established architecture.
• Create reusable components such as AI plugins, skills, GPT integrations, custom applications, backend services, and APIs for enterprise use cases.
• Use Codex and other AI development tools to accelerate implementation, testing, debugging, and documentation while maintaining engineering quality.
• Collaborate with technical leads, product managers, and partner teams to clarify requirements, evaluate approaches, and deliver features from prototyping to production rollout.
• Integrate AI models with enterprise applications, data sources, and workflows, implementing runtime and middleware patterns that support interoperability and multi-tenant scale.
• Participate in architecture and code reviews, apply secure coding practices, and follow API versioning, compatibility, deprecation, and safe rollout standards.
• Implement automated testing and AI evaluations to validate functionality, accuracy, security, reliability, and performance.
• Diagnose and resolve complex issues across models, plugins, backend services, and integrations, and translate feedback into product improvements.
• Provide logging, monitoring, usage telemetry, and observability, and contribute to service-level objectives, capacity planning, resilience, and operational improvements.
• Develop AI cost and usage intelligence, including cost attribution, forecasting, token budgets, threshold alerts, and reporting to support investment decisions.
• Implement model selection and usage controls that balance cost, quality, risk, and performance, optimizing token consumption and context through caching, context management, and workload-specific routing.
• Create technical guidance, migration guides, and adoption playbooks, sharing engineering practices that make AI capabilities easier to adopt and maintain.

What you bring

• A Bachelor’s degree (for example, B.Tech) in Computer Science/Engineering or a related field, plus at least 4 years of software development experience.
• 4+ years of experience designing, developing, and delivering backend services, APIs, distributed systems, developer platforms, or cloud services.
• 4+ years of programming experience in one or more of: Java, Python, JavaScript, or Go.
• Experience deploying applications on cloud platforms such as OCI, AWS, Azure, or Google Cloud.
• Experience with relational and/or NoSQL databases, including data modeling, querying, and integration with backend services.
• Experience with software design, API integration, automated testing, code reviews, debugging, and secure coding practices.
• Experience supporting production services with logging, monitoring, observability, incident resolution, reliability improvements, and performance optimization.
• Experience collaborating across engineering, architecture, security, product, and business stakeholders to deliver software capabilities.

Technologies you’ll work with

• OCI, AWS, Azure, Google Cloud
• Java, Python, JavaScript, Go
• Relational and NoSQL databases
• Codex, GPT, LLM
• Retrieval-augmented generation (RAG)
• Model Context Protocol (MCP)

Preferred skills

• Hands-on experience building, integrating, or operating AI-enabled applications, generative AI solutions, developer tools, or enterprise productivity applications.
• Experience using Codex (or similar AI coding tools) for development, testing, debugging, and documentation.
• Experience with LLM application patterns, including prompt design, RAG, tool/function calling, agents, memory, evaluations, and model routing.
• Experience building AI plugins, skills, GPT integrations, reusable workflows, or shared AI services.
• Experience developing Model Context Protocol (MCP) servers and tools that connect AI applications and agents with enterprise APIs, backend services, and data sources, including authentication, authorization, testing, and observability.
• Familiarity with AI control plane and data plane concepts, including integrating AI capabilities with backend services, APIs, and enterprise systems.
• Experience implementing AI security and privacy, model-access controls, and policy-based model selection.
• Experience with AI cost optimization, including token and context management, usage telemetry, cost attribution, forecasting, budgeting, and caching.

Location: Nashville, TN (onsite)