Senior AI Software Engineer

Oracle•Nashville, TN

20h

About The Position

As a Senior AI Software Engineer in an AI Innovation organization within OCI, you will help build AI capabilities into Oracle products through strong software engineering, technical leadership, and high-quality execution. This is a software engineering role for someone who can work confidently across large codebases, design reliable systems, and deliver production-ready features at speed. You will contribute to the architecture, implementation, and evolution of AI-enabled product capabilities, working closely with engineering, product, and AI teams.

Requirements

Strong software engineering skills
Technical leadership capabilities
Ability to work confidently across large codebases
Ability to design reliable systems
Ability to deliver production-ready features at speed
Experience with AI-enabled product capabilities
Experience working closely with engineering, product, and AI teams
Experience designing, architecting, and delivering scalable agentic AI systems capable of reasoning, planning, tool use, workflow execution, multi-step task orchestration, and safe human-in-the-loop escalation.
Experience serving as a technical owner for AI platform capabilities, including agent execution, inference systems, model serving, AI workflow orchestration, evaluation, and observability.
Experience building production-grade services for tool calling, agent memory, context management, Model Context Protocol (MCP) integration, vector retrieval, multi-agent coordination, policy enforcement, and evaluation.
Experience developing distributed services optimized for low latency, high throughput, GPU efficiency, reliability, cost, operability, and secure multi-tenant operation.
Experience defining service boundaries, APIs, data models, state management, consistency tradeoffs, failure modes, SLIs/SLOs, rollout strategies, and operational readiness criteria for AI platform services.
Experience integrating AI agents securely and reliably with enterprise APIs, cloud services, databases, identity systems, secrets management, and external systems.
Experience establishing AgentOps and LLMOps practices for tracing, monitoring, eval suites, regression testing, experimentation, safety guardrails, prompt/tool versioning, and production reliability.
Experience evaluating and operationalizing emerging technologies in generative AI, agentic workflows, inference optimization, long-context systems, reasoning models, AI developer tooling, and agentic-first development.
Experience driving engineering excellence through code reviews, design reviews, test strategy, deployment automation, incident analysis, documentation, and AI-assisted development practices using tools such as Codex, Claude Code, Cursor, Copilot, or similar systems.
Experience owning critical production outcomes, including reliability, performance, security posture, cost efficiency, and supportability for the systems delivered.

Nice To Haves

Experience with AI-assisted development practices using tools such as Codex, Claude Code, Cursor, Copilot, or similar systems.

Responsibilities

Design, architect, and deliver scalable agentic AI systems capable of reasoning, planning, tool use, workflow execution, multi-step task orchestration, and safe human-in-the-loop escalation.
Serve as a technical owner for OCI AI platform capabilities, including agent execution, inference systems, model serving, AI workflow orchestration, evaluation, and observability.
Build production-grade services for tool calling, agent memory, context management, Model Context Protocol (MCP) integration, vector retrieval, multi-agent coordination, policy enforcement, and evaluation.
Develop distributed services optimized for low latency, high throughput, GPU efficiency, reliability, cost, operability, and secure multi-tenant operation.
Define service boundaries, APIs, data models, state management, consistency tradeoffs, failure modes, SLIs/SLOs, rollout strategies, and operational readiness criteria for AI platform services.
Integrate AI agents securely and reliably with enterprise APIs, cloud services, databases, identity systems, secrets management, and external systems.
Establish AgentOps and LLMOps practices for tracing, monitoring, eval suites, regression testing, experimentation, safety guardrails, prompt/tool versioning, and production reliability.
Evaluate and operationalize emerging technologies in generative AI, agentic workflows, inference optimization, long-context systems, reasoning models, AI developer tooling, and agentic-first development.
Drive engineering excellence through code reviews, design reviews, test strategy, deployment automation, incident analysis, documentation, and AI-assisted development practices using tools such as Codex, Claude Code, Cursor, Copilot, or similar systems.
Own critical production outcomes, including reliability, performance, security posture, cost efficiency, and supportability for the systems delivered.

Benefits

Medical, dental, and vision insurance, including expert medical opinion
Short term disability and long term disability
Life insurance and AD&D
Supplemental life insurance (Employee/Spouse/Child)
Health care and dependent care Flexible Spending Accounts
Pre-tax commuter and parking benefits
401(k) Savings and Investment Plan with company match
Flexible Vacation
11 paid holidays
72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours.
Paid parental leave
Adoption assistance
Employee Stock Purchase Plan
Financial planning and group legal
Voluntary benefits including auto, homeowner and pet insurance