15: Optimizing AI Workloads: Balancing Cost, Performance, and Scalability with Bijit Ghosh

In this episode, Andrew Hillier and Bijit Ghosh discuss the evolving landscape of AI, discussing the growing prominence of inference over training, hybrid cloud strategies, balancing cost with performance, and the orchestration of complex hardware environments. The conversation also touches on emerging concepts like AI factories, the challenges of sovereign cloud, and how enterprises are navigating data gravity and regulatory constraints. It's a deep dive into optimizing AI infrastructure, managing costs, and the disruptive changes that are transforming both technology and business outcomes.

ABOUT OUR GUEST

Bijit Ghosh

Bijit Ghosh is a seasoned technology executive with over two decades of experience leading AI/ML, cloud, and data transformation in global financial services. As CTO – MD/Head of AI/ML, Cloud & Data Platform Engineering at Wells Fargo, he drives large-scale modernization of infrastructure and fintech platforms, applying AI Agents, cloud-native architectures, LLMOps, and DevSecOps to deliver measurable business outcomes. Bijit has a proven track record of driving more than $200M in savings through transformation, automation, and platform engineering, and he is known for empowering teams to innovate while maintaining resilience, compliance, and performance. He also contributes to open-source, writes on technology topics, and actively engages with the broader tech community.

ABOUT KUBEX TALKS

Kubex Talks is a podcast hosted by Andrew Hillier, Co-Founder and CTO of Kubex, a Kubernetes, cloud, and AI company. The podcast focuses on interviews with IT and technical leaders and innovators who have experience in delivering cloud and Kubernetes-based infrastructure within large enterprises.

LINKS

kubex.ai (http://kubex.ai)