Job Opportunities API

Why Cast AI? Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production. The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation. Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS. Global team, diverse perspectives We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead.  Unicorn momentum In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started. Join us as we build the future of autonomous infrastructure. This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, and Ukraine. About the role You'll join one of several teams building the low-level systems behind CAST AI's multi-cloud automation platform. The work sits at the intersection of Kubernetes, cloud infrastructure, and Linux. Depending on your strengths, you'll work in one of these areas: Cluster and node lifecycle - custom node bootstrapping across AWS, GCP, and Azure. Controllers and operators managing full node lifecycle. Bridging the gap between autoscaler decisions and running VMs - including working around limitations of managed Kubernetes platforms like EKS, GKE, and AKS. Cross-cloud provisioning - orchestrating infrastructure across regions and clouds. Workflow orchestration, provisioning integrations, networking and identity across cloud boundaries. Live container migration - zero-downtime relocation of running containers using CRIU checkpoint/restore, custom CRI-O and runc forks, and forked cloud CNI plugins. Memory page transfer, TCP session migration, process-level checkpoint/restore. Kernel-level Linux engineering applied to Kubernetes. Storage optimization - dynamic volume rightsizing, BtrFS compression, custom CSI drivers. Full storage stack from cloud disk APIs through filesystem internals to Kubernetes PV/PVC lifecycle. Common across all teams: Go, deep Kubernetes, multi-cloud, building beyond what the ecosystem offers. How we build We invest heavily in agentic development and AI-powered tooling. Engineers work with code agents and automated workflows daily. We expect you to shape how these tools evolve. Requirements: Strong backend fundamentals and production-grade coding, preferably Go. Hands-on Kubernetes internals, cloud infrastructure, or large-scale distributed systems experience. Clear English communication, collaborative and self-directed. Bias toward action and ownership. What would make you stand out Deep knowledge of EKS, GKE, or AKS internals. Low-level Linux experience: process internals, networking (NAT, iptables, conntrack, SDN), filesystems, storage. Kubernetes or cloud-native OSS contributions. Cloud storage depth - block storage, CSI, volume management, filesystem internals. Container runtime experience (CRI-O, runc, containerd) or CRIU. Experience with AI coding agents and agentic development workflows. Comfort building where there's no