
AI Infrastructure Hardware Engineer
About this role
AI Infrastructure Hardware Engineer is an on-site server testing and quality control position based in Hong Kong with Pragmatike for professionals experienced in GPU server manufacturing. This role suits engineering candidates with strong Linux and firmware backgrounds who prefer a hands-on physical lab and factory floor environment over remote desk work.
Role Overview
Pragmatike is hiring an AI Infrastructure Hardware Engineer on behalf of a European deep-tech enterprise that creates energy-efficient sovereign cloud infrastructure. The hiring organization designs and builds proprietary high-performance computing hardware end to end, spanning individual boards to containerized systems. This position operates on a hybrid schedule out of manufacturing sites, test labs, and factory floors in Hong Kong, requiring an immediate start date.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
About the Company
Pragmatike acts as a recruitment representative for a European deep-tech business developing vertically integrated cloud infrastructure. The hiring client manufactures custom high-performance computing hardware from the board level upward to establish a sustainable alternative to conventional cloud service providers.
How to Apply
Interested candidates should apply on the official company careers page.
Skills and tech stack
Questions candidates ask
Where is this job located?
The position is based in Hong Kong on a hybrid schedule involving the factory floor, manufacturing sites, and test lab.
What languages are required for this role?
Both fluent English and fluent Mandarin are strictly mandatory for this position.
Is this a remote or desk-based job?
No, this is not a remote or desk-based role and requires physical presence in Hong Kong on the factory floor and test lab.
What kind of hardware experience is needed?
Candidates need hands-on experience testing, validating, and performing bring-up on GPU and HPC servers, along with server architecture familiarity.
What software and technology stack is used?
The role utilizes Linux, NVIDIA software stacks, CUDA, NCCL, BIOS/UEFI, BMC/IPMI, and optional tools like Python and Bash.