AI Solutions Architect

About Cast AI Cast AI runs Kubernetes and GPU infrastructure. You see the gain in cost, performance and reliability. Cast AI acts directly in production, in real time. Scaling, rightsizing and live migration, handled on its own. Nobody gets paged in the middle of the night. Cast closes the GPU gap from both ends: sourcing capacity across clouds and regions with OMNI, and getting more out of the GPUs you already run. Every change is verified, logged and reported, so you are never guessing whether it worked.

Cast AI

Kubernetes automation platform, from CPU to GPU. Scaling, rightsizing and live migration, run autonomously.

KubernetesGPU infrastructureAI infrastructureKubernetes cost optimizationcloud cost optimizationFinOpsautoscalingrightsizingplatform engineeringEKS

C

cast.ai

201-500 employees

Software Development

Miami, FL

2019

Privately Held

47k LinkedIn followers

Raised $181M

• Lead hands-on demos of our flagship inference products - Kimchi Coding, Studio and Teleport.
• Set up Kimchi Studio workspaces within customer environments. Help teams configure worktrees, integrations (Slack, repos, docs), and skills so agents understand their conventions.
• Design and drive implementation of governance policies for customers: spending limits per team/developer, cost attribution by project, model routing preferences. Make sure the hard budget caps actually work for their org.
• Help teams integrate Kimchi's serverless inference API. Optimize model selection and routing for their specific workloads (coding, reasoning, planning tasks).
• Translate customer feedback into product input. Highlight where the agent fails, where Studio UX gets in the way, where governance policy doesn't match their needs.

• Deep hands-on experience with LLMs: you've deployed them, fine-tuned them, evaluated them, or debugged their failure modes. You care about why model A outperforms model B for a specific task.
• You know what it's like to operate in a fast-moving environment that’s prone to change.
• You've built or optimized inference systems out of curiosity. You know the difference between latency, throughput, and total cost of ownership. You ballpark costs and performance implications in your head.
• You can explain complex inference concepts to non-ML engineers and help them see why it matters to their business.
• You can think commercially. You understand revenue expansion, can identify expansion opportunities within customer organizations, and can design strategies to capture them. You're not just a technical person, you're someone who combines technical excellence with entrepreneurial thinking about growth.

• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology.
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement.
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.