As an Engineering Tech Lead (AI Infrastructure) at vCluster Labs , you aren't just a data center engineer; you are the person who builds the foundation our entire AI infrastructure product story runs on. You'll stand up our HGX-based GPU lab from the ground up, racking, cabling, and commissioning NVIDIA HGX systems, and turn that hands-on expertise into reference architectures, product guidance, and institutional knowledge the whole team can build on.
As an Engineering Tech Lead, your role will include:
GPU Lab Build-Out: Own the end-to-end setup of vCluster Labs ' HGX-based test and lab environment. You'll advise on equipment procurement, select data center colocation, specify cabling and switch configurations, and physically commission two HGX systems (eight GPUs each). This is hands-in-the-data-center work, and you'll own it start to finish.
Infrastructure Architecture: Make the critical decisions on network topology, switch selection, and hardware configuration for our HGX infrastructure. You'll know what questions to ask, what to order, and how to get these systems running at full performance.
Reference Architecture Development: Translate your hands-on HGX expertise into documented reference architectures that AI Cloud operators and enterprise AI factories can use to deploy their own infrastructure alongside vCluster Platform.
Product Influence: Work closely with engineering and product teams to inform design decisions. Your field experience with how GPU infrastructure actually gets built and operated is exactly what we need to ensure our software meets real production requirements.
Knowledge Transfer: Teach us what you know. vCluster Labs is building deep expertise in GPU infrastructure, and you'll be the primary source of that knowledge internally, through documentation, hands-on sessions, and day-to-day collaboration.
This role could be a fit for you if you bring:
HGX Systems Experience: You have physically provisioned NVIDIA HGX systems. Not just managed workloads on top of them. You were in the data center racking, cabling, and commissioning them.
Data Center Hands-On Expertise: You know how to specify cabling, connect servers to top-of-rack switches, select colocation facilities, and make infrastructure procurement decisions. This is deeply practical knowledge you've used in production.
Networking Depth: You understand the networking requirements that come with dense GPU infrastructure (InfiniBand, high-speed Ethernet, switch configuration) at the level of someone who has actually done it.
AI Cloud or HPC Background: You've worked inside an AI Cloud, HPC facility, or enterprise AI factory where you owned infrastructure at the hardware level.
Knowledge Sharer: You're energized by teaching others. You document what you know, explain your reasoning, and want the people around you to be able to do what you do.
Bonus points for: