Why this webinar exists
Top technology companies are redirecting capital toward AI Infrastructure CAPEX while slowing traditional software hiring.
The constraint is no longer models - it is infrastructure.
GPU clusters, fabrics, DPUs, and distributed systems now define competitive advantage. Yet there is a clear shortage of engineers who can operate these systems reliably.
This session helps system engineers, SREs, infrastructure engineers, and architects understand what AI Infrastructure means, why demand is accelerating, and how to transition into this domain with clarity.
This is not AI hype. This is systems engineering.
Seats are limited to 200 per session. Each person can register for one session at a time. You can switch by unregistering.
What we will cover
- What AI Infrastructure (AII) truly encompasses
- Current AI Infrastructure CAPEX landscape and industry direction
- Why GPU utilization is the core engineering problem
- Role evolution: System Engineer -> AI Infrastructure Engineer
- Certification roadmap overview (NCP AI / AIN / AIO)
- Practical learning path to enter the domain
Who should attend
- Platform and infrastructure engineers
- SRE / production engineering teams
- Data center / cluster operators
- Technical architects
- Engineers evaluating a transition into AI Infrastructure
What this session is not
- Not an AI/ML model training tutorial
- Not developer framework deep dives
- Not an introductory Kubernetes or networking class
- Not marketing
This is a strategic + technical orientation to the AI Infrastructure domain.
Format
- Duration: 40 minutes
- Live Q&A: 15-20 minutes
- Remote session
- Seats limited to 200 per session
Duration: 40 minutes + Live Q&A
AI Infrastructure is becoming the new engineering leverage layer.
The infrastructure is being built. The engineers must be ready.
Register to secure your seat.