Senior Platform Architect

About Us
Axelera AI is not your regular deep-tech startup. 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 four years, we have raised a total of $370 million and have built a world‑class team of 220+ employees (including 49+ PhDs with more than 40,000 citations), both remotely from 18 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  Senior Platform Architect  to own the platform‑level architecture of our scale‑up and scale‑out systems as we grow from single‑accelerator products to server‑ and rack‑level deployments.

In this role you will define how our current and next‑generation accelerators come together as high‑performance platforms. You own how accelerators are composed into systems to execute workloads effectively, defining system topology, host integration, memory organization and platform‑level requirements to achieve performance, scalability and operability. The role is in close collaboration with the AI Infrastructure Systems division that builds our board‑and‑system‑level products, as well as with the broader architecture teams, and the silicon and software divisions.

Finally, you will engage directly with strategic customers and ecosystem partners on architecture requirements and technical alignment.

Key responsibilities

Define the platform‑level architecture of scale‑up and scale‑out fabrics across our accelerator product line, from single‑node systems through to rack level deployments.

Specify physical interconnect infrastructure — defining the architectural requirements and trade‑offs that the AI Infrastructure Systems division executes against, including how interconnect characteristics impact system‑level workload performance.

Help translate workload and performance requirements into concrete system‑level architecture and interconnect specifications.

Define host integration, covering PCIe, CXL and memory attachment, and the system‑level memory organization across the platform.

Own platform performance, power, cost and scalability, ensuring scale‑up and scale‑out designs sustain target performance as systems grow from single nodes to large clusters.

Define operability and RAS (reliability, availability, serviceability) requirements so 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 architecture decisions, including the AI Infrastructure Systems division, silicon, product management, software, and customers, system integrators and ecosystem partners on architecture requirements — with commercial engagement and design‑in ownership sitting with the AIIS Director.

Drive methodology and best practices for platform‑level design as the team scales.

Qualifications

Experience:

Significant experience (5+ years) in system, platform, or hardware architecture, with a strong track record at server and/or rack scale.

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 Ethernet, UALink, optical, and switched‑fabric technologies, and the ability to reason about their system‑level performance trade‑offs.

Systems thinking:  Ability to connect workload characteristics to hardware architecture and to quantify the impact of design choices on end‑to‑end performance.

Leadership and collaboration:  Demonstrated ability to lead and collaborate across multidisciplinary teams and to interface effectively with partners and senior stakeholders.

Strong problem‑solving skills, a collaborative mindset,…