Lead Principal Platform Software Engineer, AI Acceleration, Developer Tools at Oracle

Department: Software Engineering

Compensation · Listed in posting

$96,800 – $306,400/yr

Location: Nashville, Tennessee
Type: Full-time
Level: lead/mgmt
Posted: Aug 14, 2026

Description

Oracle is hiring a Lead Principal Engineer to lead AI acceleration across developer tools. The role will establish architecture and technical strategy for AI agents, LLM-powered developer experiences, context and retrieval, tool integration, orchestration, evaluation, and intelligent automation; experiment with emerging technologies; translate prototypes into secure, scalable OCI services; and influence technical direction across engineering, product, AI/ML, and service teams. The position requires 12+ years of software engineering experience, strong distributed-systems and cloud or backend architecture expertise, and experience with LLMs or generative AI. The stated US hiring range is $96,800 to $306,400 per annum, with medical, dental, and vision insurance among the benefits.

Required Skills

Distributed systems
Cloud platforms
LLMs
AI agents
Context retrieval
Intelligent automation
Experimentation
Architecture reviews

Additional Information

Minimum Education: Bachelor of Science or Master of Science in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
Required Previous Experiences: 12+ years of software engineering experience
Architecting complex production systems
Providing technical leadership across multiple engineering teams
Applying or evaluating LLMs, generative AI, AI agents, or related AI technologies
Experimenting in ambiguous and rapidly changing technical environments
Influencing architecture and engineering strategy across teams without direct authority
Moving technologies from exploration and proof-of-concept through architecture, production deployment, scale, and adoption
Preferred Qualifications: Experience building AI-powered developer tools, coding agents, engineering assistants, intelligent testing or debugging systems, autonomous development workflows, or AI-driven developer productivity platforms
Deep practical knowledge of LLMs, agentic architectures, reasoning models, tool use, context engineering, retrieval, inference, orchestration, evaluation, and emerging AI software engineering patterns
Experience designing AI platform abstractions with stable interfaces, security, observability, governance, and operational reliability
Using experimentation and quantitative evaluation to decide on emerging technologies
Challenging conventional approaches and introducing new technical directions
Mentoring senior engineers and building organizational consensus around high-impact architectural decisions
Translation Company Name: Oracle

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