Principal Software Engineer - AI Infra Compute

Oracle's OCI AI Infra Compute team in Austin, TX is seeking a Principal Software Engineer to lead the design, development, and debugging of cloud infrastructure components for AI and ML workloads, with a focus on GPU delivery, health monitoring, and automation. This role also involves guiding AI-driven initiatives and mentoring engineers.

The position sits at the intersection of cloud infrastructure and AI, driving architectural improvements and hands-on execution to keep our AI platforms scalable and reliable.

Description

OCI AI Infrastructure is building a cutting-edge, ultra high performance GPU platform to support AI/ML/HPC workloads, capable of scaling from tens to thousands of GPUs without sacrificing performance. The GPU Availability and Monitoring team within the Compute Org designs architectural changes for GPU delivery, health monitoring, triage automation, and diagnostic services to run distributed AI/ML/HPC workloads across thousands of GPUs, leveraging RoCE and Infiniband.

As a valued member of our software engineering division, you will help shape the future of our technology stack and drive meaningful improvements in cloud infrastructure and automation. In this role, you will design, develop, troubleshoot, and debug software across databases, applications, tools, networks, and other cloud infrastructure components, applying AI and ML expertise to stay ahead of the curve and collaborating with teams to deliver exceptional customer experiences.

Responsibilities

• Work independently in ambiguous situations while upholding published standards and practices.
• Design, develop, troubleshoot, and debug software for cloud infrastructure components, including databases, applications, tools, and networks.
• Help define and evolve standard software engineering practices with a focus on AI-driven development.
• Develop software for tasks associated with designing, building, and debugging applications or operating systems, leveraging AI and ML techniques.
• Lead the development of critical initiatives, including:
  • Design and implement spike-detection mechanisms for provisioning failures using ML to minimize disruptions.
  • Expand integrations with Kafka to enable near real-time actions supporting 1-Day SLO hardware repairs, utilizing event-driven architecture and stream processing.
  • Develop an automated ticket routing framework powered by NLP and ML to streamline workflows and reduce operational overhead.
  • Advance dedicated initiatives through collaboration with cross-functional teams and customers, applying AI-driven insights and recommendations.
  • Leverage AI/ML to create tools that automate testing, simulate environments, and reproduce incidents, enabling focus on higher-value work and improving customer outcomes.
  • Collaborate and lead technical discussions across multiple teams to ensure seamless integrations and effective problem-solving.
  • Provide mentorship and guidance to junior engineers to promote growth and development.

Requirements

• Python
• Java
• TypeScript
• Agile Principles
• Data modeling
• Data warehousing
• Data governance
• OCI
• AWS
• Azure
• Google Cloud Platform (GCP)
• Linux
• MacOS
• Bash
• Perl
• Ruby
• Docker
• RESTful APIs
• API gateways
• API security
• Swagger/OpenAPI
• Chatbots
• Virtual assistants
• Predictive analytics
• Kafka
• RoCE
• Infiniband
• NLP
• ML

Technologies

• Oracle Cloud Infrastructure (OCI)
• AWS
• Azure
• Google Cloud Platform (GCP)
• Linux
• MacOS
• Docker
• Python
• Java
• TypeScript
• Bash
• Perl
• Ruby
• RESTful APIs
• API gateways
• API security
• Swagger/OpenAPI
• Kafka
• RoCE
• Infiniband
• Data modeling
• Data warehousing
• Data governance
• NLP
• ML
• Chatbots
• Virtual assistants
• Predictive analytics