Lead Principal Platform Software Engineer, AI Acceleration, Developer Tools

** Job Description*
* This is an emerging space where the technology, developer expectations, and best practices are changing quickly. We are looking for a technical leader who is energized by that uncertainty: someone who is willing to  
** experiment, prototype, challenge established approaches, learn quickly, and form strong technical opinions based on evidence** . You will explore new capabilities across LLMs, AI agents, reasoning systems, context and retrieval, evaluation, and intelligent automation, while determining which ideas can deliver meaningful and durable improvements to developer productivity.

Success requires more than applying existing AI technologies. You will identify where AI can fundamentally change engineering workflows, develop a technical point of view on where we should invest, and define the architectures and platform capabilities needed to move promising ideas from experimentation to production at OCI scale.

As a Lead Principal Engineer, you will  
** influence the technical direction of AI-powered developer experiences across teams and organizational boundaries** . You will work with senior engineers, engineering leaders, product managers, AI/ML teams, researchers, and OCI service organizations to identify opportunities, test hypotheses, establish architectural direction, and build alignment around consequential technical decisions.

You will remain deeply hands-on. You will build prototypes, evaluate emerging technologies, design foundational systems, and work alongside engineers to prove what is possible. Equally important, you will know when an experiment has provided enough evidence to invest, pivot, or stop-and how to turn successful experimentation into reliable, secure, scalable platform capabilities.

** Responsibilities*
* ** Responsibilities*
* +  
** Build the architecture and technical strategy for AI Acceleration across Developer Tools** , identifying where AI can materially improve developer productivity and establishing the foundational platforms, abstractions, and services required to enable those experiences.

+  
** Experiment aggressively and learn quickly
** by building prototypes, evaluating emerging models and agentic technologies, testing unconventional approaches, and using measurable results to determine which ideas should progress from exploration to production.

+  
** Create clarity from ambiguity
** by identifying high-value problems, forming technical hypotheses, challenging assumptions, evaluating competing approaches, and translating rapidly evolving AI capabilities into actionable architectural direction.

+  
** Influence technical direction across the org
** building alignment among senior engineers, engineering leaders, AI/ML teams, product organizations, and service teams around architectural choices and strategic investments without relying on direct authority.

+ Architect platforms for  
** AI agents, LLM-powered developer experiences, context and retrieval, tool integration, orchestration, evaluation, and intelligent automation** , with clear separation between rapidly evolving AI technologies and durable platform abstractions.

+ Establish a disciplined path from  
** prototype to production** , defining engineering patterns that allow successful experiments to evolve into secure, observable, reliable, cost-efficient, and scalable OCI services.

+ Raise the technical bar for AI engineering through architecture reviews, reference implementations, evaluation frameworks, technical mentorship, engineering standards, and clear communication of complex architectural tradeoffs.

+ Develop mechanisms to  
** measure whether AI actually improves the developer experience** , using evaluation, telemetry, experimentation, developer feedback, and productivity…