
201 - 500 employees
Founded 2019
☁️ SaaS
🤖 Artificial Intelligence
🤝 B2B
SaaS • Artificial Intelligence • B2B
Cast AI is a SaaS platform that automates Kubernetes application performance, infrastructure, and cost optimization for cloud-native teams. It connects to EKS/AKS/GKE and on-prem clusters with no code changes, uses predictive models and runtime signals to rightsize pods, scale nodes, optimize GPUs and Spot instances, and run approved self-healing runbooks to maintain reliability and reduce cloud spend. Cast AI targets platform, SRE, and FinOps teams and supports AI/LLM workloads, GPU optimization, and real-time workload placement and cost intelligence.
🔥 0 minutes ago
Where this job comes from
Posted on Cast AI's careers page, not through a job board
First seen by Remote Rocketship 0 minutes ago

201 - 500 employees
Founded 2019
☁️ SaaS
🤖 Artificial Intelligence
🤝 B2B
SaaS • Artificial Intelligence • B2B
Cast AI is a SaaS platform that automates Kubernetes application performance, infrastructure, and cost optimization for cloud-native teams. It connects to EKS/AKS/GKE and on-prem clusters with no code changes, uses predictive models and runtime signals to rightsize pods, scale nodes, optimize GPUs and Spot instances, and run approved self-healing runbooks to maintain reliability and reduce cloud spend. Cast AI targets platform, SRE, and FinOps teams and supports AI/LLM workloads, GPU optimization, and real-time workload placement and cost intelligence.
• Design and build systems behind the AI assistant, including agent flows, context retrieval, and live Kubernetes infrastructure data connections • Build and evolve a public, permission-aware MCP server with curated tools, identity, audit, and safety gates • Develop and maintain cloud connectivity across AWS, GCP, and Azure and the underlying data foundations • Write production Go services interacting with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time • Own features end-to-end from design through implementation, testing, and production rollout • Debug novel issues including incorrect agent answers, cross-cloud permission edge cases, and large-scale data freshness problems • Build quality harnesses with evaluations, telemetry, and feedback loops to ship agent improvements without regressions • Contribute to product direction and backlog • Participate in the team's on-call rotation
• Strong software engineering fundamentals, including clean abstractions, maintainable code, and architecture justification • Generalist comfortable debugging distributed systems, designing authentication flows, and tuning agent behavior • Production experience with Go strongly preferred; comparable systems programming skills accepted • Experience building or operating large-scale SaaS platforms in production, including multi-tenant systems and high-volume environments • Solid understanding of Kubernetes, including autoscaling, scheduling, and networking • Personally driven a complex project end-to-end • Hands-on experience with AI coding agents and agentic development workflows • Production experience with observability tooling • Experience with CI/CD and DevOps practices • Strong verbal and written English skills • Adaptable, proactive, and comfortable with ambiguity • Experience building shipped agentic systems such as MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, or evaluation frameworks • Deep hands-on experience with AWS, GCP, or Azure, including IAM, compute, networking, and APIs • Experience with LLM application quality, evaluations, prompt engineering at scale, and agent-loop latency and cost optimization • Knowledge of OAuth 2.0/OIDC and multi-tenant authorization design • Deep knowledge of EKS, GKE, or AKS internals • Kubernetes or cloud-native OSS contributions • Background check may be conducted at the final recruitment stage • Must reside in an eligible European country; Cast AI does not provide visa sponsorship or work permits
• Equity options • Flexible, remote-first global environment • 10% of work time for personal projects or self-improvement • Learning budget for professional and personal development, including international conferences and courses • Annual hackathon • Team-building budget and company events • Equipment budget • Extra days off • Work on genuinely new problems and production AI platforms • Real users and fast product delivery
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