Principal AI Agent / Software Engineer- Nashville

Oracle; Nashville (TN); On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

Job summary

Oracle Corporation in Nashville, TN seeks a Principal AI Agent / Software Engineer to lead and shape next-generation AI systems on Oracle Cloud Infrastructure (OCI). This senior, hands-on role defines architecture, builds production-grade agentic platforms, autonomous workflows, and scalable inference for enterprise applications.

You will translate ambiguous goals into durable technical strategy, guide cross-team execution without formal authority, and stay deeply involved in design, code

Qualifications

• Senior staff-level, hands-on technical leadership.
• Translate ambiguous product goals into durable technical strategy and architecture.
• Lead multi-team execution without direct authority.

Responsibilities

• Define and build production-grade agentic AI platforms on OCI.
• Architect scalable inference and enterprise AI applications.
• Lead multi-team execution with operations, reviews and incident follow-up.
• Ship, scale, and operate secure, observable AI platform systems.

Skills

Distributed systems

AI/ML engineering

LLMs orchestration

OCI cloud

Incident response

Architecture leadership

Tools

OCI

Kubernetes

Observability tools

Job description

This role in onsite in Nashville, TN.

The Principal AI Agent / Software Engineer is a Senior Staff-level, hands-on technical leadership role responsible for defining, building, and operating next-generation AI systems on Oracle Cloud Infrastructure (OCI). This person will set architecture and engineering direction for production-grade agentic AI platforms, autonomous workflows, scalable inference infrastructure, and enterprise AI applications used in large-scale, business-critical environments.

This role requires a proven engineer who can translate ambiguous product and platform goals into durable technical strategy, lead multi-team execution without direct authority, and remain deeply hands-on in design, code, reviews, operations, and incident follow-up. The ideal candidate combines deep distributed systems experience with practical AI-native engineering, including orchestration of LLMs, tools, APIs, memory, retrieval, evaluation, guardrails, and cloud services. The expectation is to ship, scale, and operate reliable, secure, observable, and cost-aware AI platform systems while raising the technical bar for engineers across the organization.

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