Software Developer 3, AI Infrastructure

Oracle Oracle · Enterprise · Austin, TX +1

Software Developer role focused on building and scaling AI infrastructure, specifically GPU clusters and related control/data planes, to support customer AI workloads. The role involves designing and developing large-scale distributed software services for managing this infrastructure, ensuring top performance, reliability, and scalability.

What you'd actually do

  1. Design and develop large-scale distributed software services and solutions to manage AI infrastructure of OCI.
  2. Write high quality and maintainable code by leveraging design reviews, code reviews, unit tests and integration tests.
  3. Develop complete solutions by ensuring that the services and the components are well-defined and modularized, secure, reliable, diagnosable, actively monitored, compliant and reusable.
  4. Focus on customer needs through a data driven approach.
  5. Collaborate with other team members working on the same project to meet customer requirements.

Skills

Required

  • BS (or equivalent experience) in Computer Science, Engineering, or related field.
  • 3 years of experience in software development with programming languages including, but not limited to, C, C++, C#, Java, Go, Rust.
  • 1 year of experience designing and developing distributed systems and services.
  • Strong problem-solving and troubleshooting skills, with the ability to analyze complex systems and identify areas for improvement.
  • Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams.

Nice to have

  • Experience in managing cloud infrastructure with hundreds of thousands of servers.
  • Experience in containerization technologies such as Docker and Kubernetes.
  • Experience in scheduling high-performance workloads on Kubernetes or Slurm.

What the JD emphasized

  • scale and optimize AI infrastructure components
  • GPU control plane and GPU data plane
  • customer AI workloads
  • scale from tens to thousands of GPUs

Other signals

  • building the world's largest AI clusters
  • GPU focused cloud
  • scale from tens to thousands of GPUs
  • scale and optimize AI infrastructure components
  • GPU control plane and GPU data plane
  • customer AI workloads
  • scheduling high-performance workloads