GPU Stack CI Infrastructure Engineer
Listed on 2026-05-19
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Software Development
DevOps, Cloud Engineer - Software, Software 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. AMD’s AI software stack is moving fast — and keeping pace means shipping complete, validated GPU stack releases to customers as quickly as the software can evolve. Getting there requires validating not just ROCm, but the full recipe: firmware, kernel driver, and ROCm together, across multiple GPU products, with confidence that what ships to customers actually works as a coherent system.
WhatYou’ll Do
- Get nightly CI running, fast — the first priority is standing up nightly integration builds for the unified GPU stack. You’ll own that end‑to‑end: the pipeline, the scheduling, the result reporting, and the Last Known Good (LKG) manifest promotion that gives every engineer a trusted baseline.
- Solve the runner provisioning problem — standard cloud runners can’t build firmware. You’ll work directly with IT to provision Git Hub Actions self‑hosted runners that handle the real constraints: NFS mounts for host‑side tools, code‑signing pipelines, network access, and permissions that firmware builds require. This is the kind of infrastructure work that requires both technical depth and the ability to get things done across organizational boundaries.
- Build toward AWS‑aligned infrastructure — the broader GPU stack CI is moving toward AWS‑hosted runners. You’ll make sure Under The Rock ’s infrastructure is consistent with that direction from the start, rather than creating something that has to be rebuilt later.
- Own the CI, not just contribute to it — nobody else on the team is currently focused on CI. You’ll be setting the direction, making the tooling choices, and shipping the automation that everything else depends on.
- 8+ years of software engineering or infrastructure engineering experience
- Strong coding ability — you’ll be writing automation, not clicking through UIs
- Deep knowledge of CI/CD pipeline design and Git Hub Actions (or comparable platform)
- Experience provisioning and maintaining self‑hosted runners or build infrastructure at scale
- Comfort navigating complex infrastructure environments — network permissions, NFS mounts, firewall rules, signing pipelines
- Strong problem‑solving and communication skills across engineering and IT stakeholders
- Fluency with agentic AI workflows (Cursor, Claude, Copilot, etc.) as a force multiplier for engineering throughput
- Experience setting up CI infrastructure on AWS (EC2‑based runners, IAM, networking)
- Familiarity with firmware signing pipelines and firmware release processes — understanding how signing fits into a CI workflow is a meaningful advantage given the constraints of this environment
- Familiarity with firmware or kernel build environments and their infrastructure constraints
- Experience integrating CI systems with hardware‑in‑the‑loop testing
- Sharpen your agentic AI engineering skills — standing up CI infrastructure across a complex, multi‑layer stack means writing a lot of automation fast: runner provisioning scripts, workflow templates, integration glue, monitoring. This is exactly the kind of work where engineers who pair well with AI coding agents move dramatically faster than those who don’t. You’ll be using these tools daily in a production‑grade, high‑stakes environment — and building a depth of experience in AI‑assisted engineering that is hard to get anywhere else.
- High ownership — you’re building the foundation, not maintaining someone else’s system
- Customer‑facing impact — the CI…
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