AI Infrastructure Engineer

• Experience in DevOps, Platform, or Infrastructure Engineering.
• Deep hands-on experience with Kubernetes and container orchestration at scale.
• Proven ability to design and deliver platform features that serve internal customers or developer teams
• Experience building developer-facing platforms or internal developer portals (e.g.custom workflow tooling).
• Hands-on experience in storage or network engineering within Kubernetes environments (e.g., CSI drivers, dynamic provisioning, CNI plugins, or network policy).
• Experience with Infrastructure as Code tools like Terraform.
• Background in HPC, Slurm , or GPU-based compute systems for ML/AI workloads.
• Practical experience with monitoring and observability tools (Prometheus, Grafana, Loki, etc.).
• Understanding of machine learning frameworks (PyTorch, vLLM, SGLang, etc.).

• Bachelors or Masters degree in Computer Science, Computer Engineering, or a related field.

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Benefits offered are described: AMD benefits at a glance .

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position.

AMD’s “Responsible AI Policy” is available here.

This posting is for an existing vacancy.