Senior Field Applications Engineer, Datacenter & AI Systems Debug and Deployment Support

Amd

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Austin, TX
Salary
$114,400–$171,600 / yr
Posted
8 days ago
Freshness
Confirmed live yesterday
Closes
Sep 3, 2027

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $194k
This role $143k
$100k most similar roles pay here $245k

This role pays less than 82% of similar roles. Most pay $157,425–$231,150 — the shaded band above. At the midpoint, this role pays about $143k versus about $194k for comparable roles.

Based on 240 similar postings.

Employer

About Amd

AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors

Amd currently has 367 open roles on FindRole.

Listed pay typically runs $166,400–$249,600 across 367 roles with salary data.

Most-posted roles

View all roles at Amd

At a glance

TL;DR · Senior Field Applications Engineer, Datacenter & AI Systems Debug and Deployment Support

Sr. Field Applications Engineer, Datacenter & AI Systems Debug and Deployment Support joins the Global Partner Support team to provide technical expertise at the intersection of data center hardware, system software, and AI workloads. This role involves debugging, triaging, and resolving complex issues involving AMD Data Center GPUs and the AI software stack across single-node and multi-node environments. Responsibilities include reproducing issues in lab environments, analyzing logs and core dumps, collaborating with engineering teams to validate fixes, and supporting large-scale cluster bring-up activities. The role requires proficiency in Linux systems, command-line tools, and low-level debugging using gdb. Candidates should possess knowledge of GPU architecture, PCIe topologies, and memory hierarchies. Required skills include experience with PyTorch or TensorFlow, programming in Python, C/C++, or Java, and familiarity with Git, while technical depth involves supporting AI training environments and inference deployments.

What you'll do

  • Debug system-level issues involving GPUs, drivers, networking, and AI software in single and multi-node environments.
  • Provide post-sales technical support to cloud providers, OEMs, ODMs, and enterprise customers.
  • Reproduce customer issues in lab environments by analyzing logs, core dumps, and performance data.
  • Collaborate with internal engineering teams to resolve bugs and validate technical fixes.
  • Document debug methodologies and technical findings for internal knowledge bases.
  • Support large-scale cluster bring-up activities and new product introductions.
  • Develop and deliver technical training sessions on products and troubleshooting methods.

What we're looking for

  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field.
  • Knowledge of CPU and GPU architecture concepts, memory hierarchies, and system-level behavior.
  • Experience with Linux systems, command-line tools, system administration, and low-level debugging using kernel logs and gdb.
  • Working understanding of server and accelerator architectures including PCIe topologies, CPU-GPU interconnects, and NUMA concepts.
  • Familiarity with AI or HPC workloads and frameworks such as PyTorch or TensorFlow.
  • Proficiency in at least one programming language such as Python, C/C++, or Java.
  • Experience using source control systems like Git.
  • Strong analytical, problem-solving, and communication skills to work with technical customer and partner teams.

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