AI teams often know the outcomes they want to achieve before they know the infrastructure they need to get there. In Episode 18 of the AI Cloud Essentials Podcast, host Ritu Jyoti sits down with Tara Madhyastha, Senior Field Engineer and Solutions Architect at CoreWeave, to explore how hands-on technical partnership can turn ambitious AI goals into scalable architectures.
Learn how CoreWeave field engineering works alongside customers to design, test, troubleshoot, and scale infrastructure for demanding workloads across training, inference, physical AI, robotics, healthcare, and more. Tara also explains why successful AI infrastructure requires more than performance and capacity—it takes the right combination of compute, storage, networking, operations, and trusted technical guidance.
What you’ll learn
- How field engineering helps turn AI goals into infrastructure architectures
- Why performance and capacity are only part of scaling AI successfully
- How AI-native cloud brings compute, storage, networking, and operations together
- Why hands-on collaboration can help teams move from POC to production faster
- What AI teams should consider as workloads and infrastructure requirements evolve
Guest: Tara Madhyastha, PhD, Senior Field Engineer and Solutions Architect, CoreWeave
