System Design Engineer - AI Cluster Software Engineer

Advanced Micro Devices, Inc•Santa Clara, CA

2d•Hybrid

About The Position

This is a hands-on role for a full-stack developer to create and deliver a range of tools and applications focused on design and deployment of large-scale AI/ML clustered infrastructure. You will be working with the latest agentic tools and patterns to develop, deploy, and maintain these applications. You’ll join a growing team of multi-disciplined engineers that operates across industry verticals as subject matter experts in the AI stack and across the cluster.

Requirements

Demonstrated use of AI coding assistants and LLM-powered developer tools: daily user of AI agents and tools
Five or more years of professional software development experience, including substantial experience building and supporting web applications
Proficiency in modern frontend development using JavaScript or TypeScript and a framework such as React, Angular, or Vue
Experience developing backend services and APIs using a modern server-side language or framework
Experience deploying and operating applications using Linux, containers, CI/CD, and cloud or on-premises infrastructure
Experience with automated testing, source control, code review, debugging, and production support
Working knowledge of web application security, authentication, authorization, and secure secrets handling

Nice To Haves

Strong Linux fundamentals: Linux operating systems, networking, filesystems, containers, performance tooling (perf, flamegraphs, nvprof/rocprof, basic eBPF).
Clear communication: ability to turn complex systems into accessible, structured documentation with diagrams and reproducible steps
AMD ecosystem experience: ROCm, RCCL, Instinct GPUs, EPYC platforms, compiler/toolchain impacts, and performance tuning
Orchestration models: Slurm configuration patterns, Kubernetes for HPC/AI (GPU operators, device plugins), Apptainer/Singularity
Automation, IaC , and scripting tools/languages (Ansible, Terraform, Python, bash)
Storage/data: knowledge of or familiarity with parallel filesystems (Lustre, BeeGFS), object stores, RDMA, data pipeline throughput and caching strategies
Hands-on familiarity with on-premises infrastructure, particularly for AI/ML/HPC workloads would be beneficial

Responsibilities

Partner with engineering peers, domain experts in adjacent teams, and business stakeholders to understand requirements and translate them into flexible, future-proof design solutions
Hands on development, iteration, and maintenance of tools and applications that codify various aspects of large-scale AI cluster design stages and cluster deployment activities
Design and development of cohesive interface code between disparate third party tools
Own features from requirements and design through deployment and ongoing maintenance
Work in an iterative software environment, including planning and delivering work in small increments, collaborating with stakeholders, often in different areas of domain expertise (Agile development practices)
Participate in code reviews and retros; adapt to changing requirements and priorities