🛠 Tech Stack

💼 About This Role

You'll lead end-to-end GPU infrastructure deployments for neocloud and AI Factory customers, from bare metal to production. You'll drive proof of value engagements that directly shape the product roadmap. This role combines pre-sales technical depth with hands-on engineering at the earliest stage of customer adoption.

🎯 What You'll Do

• Lead end-to-end technical deployments on bare metal GPU nodes
• Configure and troubleshoot GPU operator, CNI, and distributed storage
• Deploy and validate Kubernetes and vCluster for managed K8s
• Document reusable playbooks and deployment architectures

📋 Requirements

• 5+ years deploying Kubernetes in production
• Practical knowledge of NVIDIA GPU Operators and CUDA tooling
• Deep understanding of CNI plugins and overlay networks
• Experience with persistent volume configuration and CSI drivers

✨ Nice to Have

• Automation with Bash, Python, or Go
• CKA certification or experience writing Kubernetes Operators
• Familiarity with inference serving and LLM deployment tooling

🎁 Benefits & Perks

• 💰 Competitive Salary with equity and bonus
• 🏥 Platinum-Level Insurance (health, dental, vision, life)
• ⏰ Flexible Working Schedule
• 🏠 Workplace Flexibility (remote-first)

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Screen· 60 min
3. 3On-site Interview· half day