Cast AI automates Kubernetes infrastructure decisions across AWS, GCP and Azure, replacing manual tuning with continuous optimization. Its stack pairs a cloud-native core (Kubernetes, gRPC, ArgoCD, Prometheus/Grafana) with LLM-serving engines like vLLM, SGLang and TensorRT-LLM, signaling a push into GPU and AI inference optimization. Hiring is accelerating, senior-weighted and split between engineering and sales, with a heavy Central and Eastern European footprint.
Cast AI, founded in 2019 and headquartered in Miami, FL, builds an automation platform that keeps cloud-native and AI workloads reliable and performant while lowering cloud spend. The product targets teams running Kubernetes on managed services such as EKS-class AWS clusters, GKE and AKS, and supports multi-cloud environments. Core capabilities include workload autoscaling, storage optimization, live container migration and cross-cloud provisioning. The privately held company employs 201–500 people and hires across the United States, Europe and Asia-Pacific.
Cast AI runs on Kubernetes, Python, gRPC, PostgreSQL and ClickHouse across AWS, GCP and Azure, with GitLab CI/CD, ArgoCD, Prometheus and Grafana, plus vLLM, SGLang, TensorRT-LLM and PyTorch for AI workloads.
Job posts point to a workload autoscaler, storage optimization, live container migration, cross-cloud provisioning, a Terraform provider and Karpenter integration.
Cast AI hires in the United States, Lithuania, Poland, Slovenia, Slovakia, Romania, Bulgaria, Hungary, Croatia, Latvia, India, South Korea, Singapore and Australia.
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Cast AI's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.
