Senior Agentic System & Application Engineer

WHAT YOU DO AT AMD CHANGES EVERYTHING 

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems

Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary

When you join AMD, you’ll discover the real differentiator is our culture

We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives

Join us as we shape the future of AI and beyond.  Together, we advance your career.  

Senior Agentic System & Application Engineer 

Role Description 

We are seeking a Senior Software Development Engineer to build agentic AI systems that make HPC and GPU workloads easy to run and fast to execute

You will design and deploy autonomous pipelines that set up environments, compose and launch jobs, debug failures, profile performance, and ship validated optimizations into applications, libraries, and CI/perf gates

The role spans agent architecture (planning, tool-use, memory), LLM inference/serving, HPC integration (schedulers, containers), and performance tooling

You will work close to runtimes and compilers to enable kernel-level interventions, including tuning and code generation where appropriate, with strong correctness guarantees, reproducibility, and observability

You will also contribute to developing advanced agentic technologies and systems for diverse use cases beyond the scenarios above. 

Key Responsibilities 

• Build agentic frameworks for planning, tool-use, memory, and long-running workflow execution. 

• Automate env setup, containerization, and reproducible dependency resolution for target workloads. 

• Compose scheduler jobs and launch runs with resource-aware configuration and policy constraints. 

• Diagnose failures from logs/telemetry, propose fixes, and automate safe remediation loops. 

• Profile bottlenecks, apply optimizations, and benchmark candidates with variance control. 

First 6-Month Goals 

• Ship an onboarding MVP: env + container + job compose/launch + failure triage, with reproducible run bundles. 

• Deploy to 1 production workloads; cut time-to-first-successful-run and deliver measurable speedups. 

• Add optimization loop for one hotspot kernel with correctness tests, rollback, and perf regression gates. 

Collaboration 

You will partner with the Platform team to deploy safely on shared clusters, with the Performance team to define benchmarks and variance controls, with the Compiler team to land codegen improvements, and with the Runtime team to expose tuning and debugging surfaces. 

Required Qualifications 

• MS/PhD (or equivalent) in CS/CE/EE or related field. 

• Shipped production agentic AI systems: orchestration, tool-use, memory, and long-horizon reliability. 

• Built LLM inference/serving on premise or using cloud APIs, with fallbacks, rate-limit handling, and observability. 

• Strong Python plus one system language: C/C++ or Rust/Go. 

• Delivered reliable systems with evals, regression gates, CI/CD, and incident-grade debugging.