Director of Hardware Engineering for AI Infrastructure Systems
European AI-semiconductor company building AI inference accelerators and software for embedded, edge, server, and data-center deployments.
Funding history
About Axelera AI
Axelera AI develops purpose-built AI acceleration hardware and the Voyager SDK for computer-vision, generative-AI, and other inference workloads, emphasizing power- and thermally-constrained deployments.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will establish and lead an infrastructure systems engineering division. You will define board- and system-level product roadmaps, review designs, lead validation and production readiness, shape platform firmware and thermal strategies, and work directly with customers and manufacturing partners.
Requirements
- 15+ years of hardware engineering experience for complex electronics products.
- At least 5 years of senior leadership experience running multidisciplinary teams.
- Experience shipping datacenter- or server-class compute hardware into volume production.
- Expertise in PCIe, CXL, high-speed SerDes, server memory, power delivery, VRM design, PCB layout and SI/PI.
- Experience with BMC management, Redfish, IPMI, UEFI, BIOS, secure boot and RAS.
- Knowledge of datacenter thermal and mechanical design.
- Experience working with tier-1 CMs and ODMs.
- Ability to review schematics, layouts, simulations and lab validation data.
- Fluent English.
Responsibilities
- Build, structure and mentor a multidisciplinary infrastructure systems engineering organization.
- Define the roadmap for PCIe accelerator cards, OAM modules, baseboards and rack systems.
- Lead system implementation across schematics, PCB design, high-speed signaling, memory, power and thermal integration.
- Own execution from concept through validation, qualification and mass-production readiness.
- Drive BMC management, platform firmware, secure boot, RAS and telemetry engineering.
- Lead thermal and mechanical strategies for high-power accelerator platforms.
- Align board and system execution with embedded AI engineering leadership.
- Refine platform requirements with architecture, product, silicon, SDK and software stakeholders.
- Engage customers, integrators, hyperscalers, cloud operators and OEM/ODM partners.
- Define engineering processes, documentation standards, validation methods and quality gates.
- Resolve technical risks, escalations and root-cause investigations.
- Own engineering budget, capital expenditure, external spend and vendor relationships.
Benefits
- Pension plan.
- Employee insurances.
- Option to receive company shares.