🛠 Tech Stack

💼 About This Role

You'll lead the design and deployment of large-scale GPU-based AI infrastructure for enterprise customers. You'll shape architecture decisions and troubleshoot performance challenges for cutting-edge AI clusters. This role offers hands-on exposure to real-world large-scale AI deployments.

🎯 What You'll Do

• Lead end-to-end design and deployment of GPU-based AI and HPC infrastructure.
• Serve as primary technical advisor for customers on architecture and optimization.
• Collaborate with cloud partners on data center compute, storage, and networking.
• Troubleshoot and optimize compute and networking performance across GPU clusters.

📋 Requirements

• 5+ years in solution architecture, systems engineering, or technical pre-sales.
• Strong understanding of GPU/CPU server architecture and system-level computing.
• Experience with data center networking (Ethernet, InfiniBand) and infrastructure design.
• Knowledge of Linux systems, kernel-level concepts, and system software.

✨ Nice to Have

• Hands-on experience with AI/HPC infrastructure deployment.
• Familiarity with GPU ecosystems, networking technologies, and cluster management tools.
• Experience with DevOps/MLOps tools such as Docker and Kubernetes.

🎁 Benefits & Perks

• 💰 Competitive base salary aligned with experience and location.
• 📈 Equity opportunities as part of total compensation.
• 🏥 Comprehensive health, dental, and vision coverage.
• 🌱 Professional growth and continuous development focus.
• 🚀 Exposure to cutting-edge AI infrastructure and large-scale global deployments.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3System Design Interview· 60 min