Engineering Tech Lead; AI Infrastructure

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.

• GPU Lab Build‑Out: Own the end‑to‑end setup of vCluster Labs' HGX‑based test and lab environment. 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. Know what questions to ask, what to order, and how to get these systems running at full performance.
• Reference Architecture Development: Translate 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. Use field experience with GPU infrastructure to ensure software meets real production requirements.
• Knowledge Transfer: Teach internal teams through documentation, hands‑on sessions, and day‑to‑day collaboration. Become the primary source of GPU infrastructure expertise.

• HGX Systems
  
  Experience:
  
  Physically provision NVIDIA HGX systems, including racking, cabling, and commissioning.
• Data Center Hands‑On Expertise: Specify cabling, connect servers to top‑of‑rack switches, select colocation facilities, and make infrastructure procurement decisions.
• Networking Depth: Understand networking requirements for dense GPU infrastructure (Infini Band, high‑speed Ethernet, switch configuration).
• AI Cloud or HPC Background: Own infrastructure at the hardware level in an AI Cloud, HPC facility, or enterprise AI factory.
• Knowledge Sharer: Energized by teaching others, documenting, explaining reasoning, and enabling teammates to perform the same work.

• Software Depth: Familiarity with Kubernetes, GPU scheduling (MIG, time‑slicing), or software stack that runs on top of HGX systems.
• Customer‑Facing
  
  Experience:
  
  Build or present reference architectures directly to enterprise customers.
• NVIDIA Ecosystem Relationships: Existing connections at NVIDIA or within the AI infrastructure community.

• Competitive Salary
  :
  Competitive compensation package, including equity.
• Platinum‑Level Insurance
  :
  Health, dental, vision, and life insurance with plans for you and eligible dependents (benefits vary by country).
• Flexible Working Schedule
  :
  Results‑based work environment allows flexibility for personal appointments and errands.
• Workplace Flexibility
  :
  Flexible work location to accommodate changing life circumstances.