At a Glance
- Tasks: Lead the architecture for cutting-edge datacentre AI accelerator systems and collaborate with diverse teams.
- Company: Join Axelera AI, a forward-thinking company driving innovation in AI technology.
- Benefits: Attractive compensation, pension plan, employee insurances, and share options.
- Other info: Embrace diversity in an open culture that fosters creativity and innovation.
- Why this job: Make a real impact in AI while working flexibly from various European locations.
- Qualifications: 5+ years in system architecture with strong leadership and collaboration skills.
The predicted salary is between 80000 - 100000 £ per year.
We are looking for a Senior Platform Architect to own the platform-level architecture for our datacenter AI accelerator systems — from server through rack integration and, eventually, full datacenter deployment. The role sits within the System Architecture team, and marks our expansion from edge AI into the datacenter. You'll take compute, memory, and connectivity requirements defined by the broader System Architecture team and translate them into architectural requirements on our hardware 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 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 architecture requirements and technical alignment.
Key responsibilities- Define the platform-level architecture for our datacenter AI accelerator systems, spanning server board design, rack integration, and datacenter-level deployment.
- Translate system-level compute, memory, and interconnect requirements — defined in collaboration with the broader System Architecture team and product division — into concrete hardware platform specifications.
- 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.
- Define host, storage and networking integration and organization at the hardware level, covering PCIe and CXL, as well as system-level power budgeting.
- Ensure scaled-up and scaled-out designs sustain target performance as 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 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.
- Drive methodology and best practices for platform-level design as the team scales.
- 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.
- Deep, hands-on understanding of Ethernet, UALink, optical, and switched-fabric technologies, and the ability to reason about their system-level performance trade-offs.
- Ability to connect workload characteristics to hardware architecture and to quantify the impact of design choices on end-to-end performance.
- Demonstrated ability to lead and collaborate across multidisciplinary teams and to interface effectively with partners and senior stakeholders.
- Bonus: Experience architecting AI/HPC accelerator systems, familiarity with distributed training/inference workloads, and exposure to data-center-scale deployment.
- Strong problem-solving skills, a collaborative mindset, and a passion for building systems at scale.
We offer a flexible working arrangement, with options to work from one of our Axelera AI offices or fully remotely from any European country you are already in. Priority will be given to candidates who are based in Belgium or Italy.
We offer an attractive compensation package, including a pension plan, extensive employee insurances and the option to get company shares. An open culture that supports creativity and continual innovation is awaiting you. Collaborative ownership and freedom with responsibility is characteristic for the way we act and work as a team.
At Axelera AI, we wholeheartedly embrace equal opportunity and hold diversity in the highest regard. Our steadfast commitment is to cultivate a warm and inclusive environment that empowers and celebrates every member of our team. We welcome applicants from all backgrounds to join us in shaping the future of AI.
Senior Platform Architect in London employer: Axelera AI
Axelera AI is an exceptional employer that fosters a culture of creativity and innovation, making it an ideal place for a Senior Platform Architect to thrive. With flexible working arrangements across multiple European locations, competitive compensation packages, and a strong commitment to diversity and inclusion, employees are empowered to take ownership of their work while enjoying ample opportunities for professional growth and collaboration within multidisciplinary teams.
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We think this is how you could land Senior Platform Architect in London
✨Join Local Tech Meetups
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We think you need these skills to ace Senior Platform Architect in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Axelera AI.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Axelera AI and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Axelera AI
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Axelera AI uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.