Principal Software Engineer, AI Core Infrastructure

Build and scale software platforms that power AI infrastructure operations. In this Principal Software Engineer role at Oracle (onsite in Nashville, TN), you will design and deliver production services and automation for provisioning, validation, troubleshooting, and ongoing operations. You will help transform complex operational processes into reliable AI-driven services, automated workflows, and AI agents that improve GPU infrastructure health visibility, accelerate investigations, and support safer, more effective corrective actions.

What You’ll Do

• Own the architecture and delivery of services and automation that support AI infrastructure provisioning, validation, troubleshooting, and ongoing operations.
• Build reliable APIs, backend services, integrations, and tools that connect infrastructure systems and convert operational data into actionable workflows.
• Develop AI-assisted capabilities for investigation, knowledge retrieval, and workflow execution, with evaluation, access controls, and human oversight.
• Replace recurring manual tasks with reusable automation, using operational feedback to prioritize improvements.
• Design systems for partial failures, retries, idempotency, auditability, observability, and safe recovery.
• Lead technical initiatives from problem definition through implementation, rollout, and production support.
• Establish engineering standards via design reviews, code reviews, testing, and clear technical documentation.
• Mentor engineers and align technical decisions with partner teams.
• Measure outcomes through reduced manual effort, faster resolution, improved reliability, and adoption by operational users.

AI Infrastructure and OCI Services

• Lead architecture, design, and development of OCI services that support AI infrastructure operations at scale.
• Build AI-driven services, automated workflows, and AI agents to help engineers assess GPU infrastructure health, investigate issues, and take corrective action.
• Design dependable distributed systems and APIs integrating infrastructure telemetry, inventory, diagnostics, and operational data.
• Translate complex operational needs into clear technical requirements and deliver solutions from concept through production.
• Develop safeguards for AI-driven actions, including access controls, evaluation, auditability, and human oversight.
• Own service reliability, performance, scalability, and security through testing, observability, safe deployments, and production support.
• Partner with operations and infrastructure teams to identify recurring problems and replace manual processes with reusable automation.
• Set technical direction, lead design and code reviews, and mentor engineers to strengthen engineering practices.
• Continuously measure and improve outcomes, including reduced manual effort, faster issue resolution, and increased infrastructure availability.

Required Qualifications

• 7+ years of professional software engineering experience, including ownership of complex production systems.
• Strong programming skills in Python, Java, Go, or a comparable language.
• Experience designing and operating distributed systems, backend services, and APIs.
• Strong understanding of data modeling, SQL, asynchronous processing, and integration across multiple systems.
• Experience with Linux, containers, Kubernetes, and cloud infrastructure.
• Demonstrated ability to diagnose production issues involving application behavior, infrastructure, and data dependencies.
• Experience delivering secure, maintainable software with automated testing, deployment pipelines, monitoring, and operational documentation.
• Ability to lead technical work across teams, make sound architectural tradeoffs, and deliver under ambiguous requirements.
• Clear written and verbal communication skills, including experience mentoring engineers.
• Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.

Preferred Qualifications

• Experience with GPU infrastructure, AI/ML platforms, HPC, or large-scale data center environments.
• Experience building infrastructure automation, orchestration platforms, or event-driven workflows.
• Experience delivering LLM applications or AI agents, including tool integration, retrieval, evaluation, and production monitoring.
• Familiarity with infrastructure inventory, telemetry, incident management, or hardware lifecycle systems.
• Experience with OCI or another major cloud platform.

Technology Stack

Python, Java, Go, SQL, Linux, containers, Kubernetes, cloud infrastructure, OCI