System Architect – Datacenter Hardware

About Us

Axelera AI https://www.axelera.ai is not your regular deep-tech company. We are creating the next-generation AI platform to support anyone who wants to help advancing humanity and improve the world around us.

In just five years, we have raised a total of $370 million and have built a world-class team of 250+ employees (including 60+ PhDs with more than 40,000 citations), both remotely from 20 different countries and with offices in Belgium, France, Switzerland, Italy, the UK, headquartered at the High Tech Campus in Eindhoven, Netherlands.

We have also launched our Metis™ AI Platform, which achieves a 3-5x increase in efficiency and performance, and have visibility into a strong business pipeline exceeding $100 million.

Our unwavering commitment to innovation has firmly established us as a global industry pioneer.

Are you up for the challenge?

Position Overview

We are looking for a System Architect – Datacenter Hardware to own hardware architecture for our datacenter AI accelerator systems — from server through rack architecture and, eventually embedded in full datacenter deployments.

The role sits within the System Architecture team and marks our expansion from edge AI into the datacenter. You'll take compute, memory, and interconnect and fabric requirements defined by the broader System Architecture team and translate them into architectural requirements on our datacenter-grade hardware platforms. You own how accelerators are composed into datacenter systems to execute workloads effectively. You own architecture of our server and rack-level solutions, including their system topology, host integration, memory organization, to achieve performance, scalability, and operability across scaled-up and scaled-out deployments.

The role is primarily in close collaboration with the AI Infrastructure Systems (AIIS) division that builds our board- and system-level products, as well as with the silicon and software divisions. Finally, you will be engaged with strategic customers and ecosystem partners on architectural requirements and technical alignment.

Key responsibilities:

• Define the hardware architecture of our AI accelerator systems, spanning server board design, rack integration, and datacenter-level deployment.
• Translate system architecture requirements for compute, memory, and interconnect/fabric, defined in collaboration with the broader system architecture team and product division, into concrete hardware specifications.
• Specify physical interconnect and fabric infrastructure, defining the architectural requirements and trade-offs that the AI Infrastructure Systems division executes against, including how interconnect and fabric characteristics impact system-level workload performance across scale-up and scale-out topologies.
• Define host, storage, and networking integration and organization at the hardware level, covering PCIe and CXL interconnect standards, as well as system-level power budgeting.
• Ensure scale-up and scale-out designs sustain target performance as datacenter systems grow from single nodes to large clusters.
• Define operability and RAS (reliability, availability, serviceability) requirements across redundancy architecture, hot-swap capability, telemetry and management interfaces (BMC/IPMI/Redfish), and fault containment to ensure datacenter platforms are manageable and dependable in production.
• Take a leading technical role in the system architecture team, interfacing directly with key partners and internal stakeholders to align on architectural decisions on the datacenter hardware. This includes interactions with the AI Infrastructure Systems division, silicon, product management, software, and customers, system integrators, and ecosystem partners on architecture requirements — with commercial engagement and design ownership sitting with the AIIS Director.
• Drive methodology and best practices for datacenter system architecture as the team scales.

Qualifications:

• Experience: Significant experience (5+ years) in system architecture or hardware architecture, with a strong track record at server and/or rack scale in datacenter environments.
• Core knowledge: Scale-up and scale-out system design, distributed workload mapping, functional partitioning, and interconnect/fabric architecture.
• Fabrics & interconnect: Deep, hands-on understanding of PCIe, CXL, Ethernet, UALink, optical, and switched-fabric interconnect technologies, and the ability to reason about their system-level performance trade-offs in scale-up and scale-out datacenter deployments.
• RAS & operability: Familiarity with RAS (reliability, availability, serviceability) principles, redundancy architecture, and management/telemetry interfaces (BMC/IPMI/Redfish) in datacenter or server platform contexts.
• Systems thinking: Ability to connect workload characteristics to hardware architecture and to quantify the impact of design choices on end-to-end …