Senior Kubernetes Engineer

Dynamo AI is building the future of secure, scalable AI systems. Our platform helps enterprises safely deploy powerful AI models in production — with reliability, control, and trust at the core. We're a team of builders working at the intersection of machine learning, infrastructure, and security.As a Senior Kubernetes Engineer, you’ll lead the full onboarding journey for our enterprise customers — from first engagement to successful production rollout. You will own the deployment of Dynamo AI clusters (Kubernetes-based) into customer environments and serve as the technical bridge between our product and the customer’s infrastructure.This is a deeply hands-on and customer-facing role. You'll work with Kubernetes, Helm, and cloud-native tools to deliver secure, scalable deployments of cutting-edge AI systems. You’ll partner with engineering, product, and leadership to bring customer feedback directly into our roadmap — and shape how AI is adopted across industries. Serving this role, you will grow into an expert of building the most cutting-edge enterprise-level AI systems.We require this role to come to the office in San Francisco at least 2 days each week.

Responsibilities

• Design and implement scalable architectures for securely running Dynamo AI in customer Kubernetes environments (EKS, AKS, GKE, on-prem) — powering large-scale, real-world use cases.
• Engage deeply with customers to understand their infrastructure, goals, and constraints — and lead hands-on implementation to get Dynamo AI into production.
• Continuously evolve our core infrastructure to ensure best-in-class performance, scalability, and security.
• Develop next-generation deployment models to enable automated, highly scalable, and repeatable rollouts of Dynamo AI clusters.
• Collaborate across product, engineering, and ML teams to design features and capabilities that solve real customer pain points.
• Serve as a trusted technical advisor during pre-sales conversations and proof-of-concept (POC) deployments

Qualifications

• 4+ years experience in solution architecture, DevOps, or cloud engineering roles.
• 2+ years experience directly working with customers.
• Great expertise of Kubernetes, Helm, and containerized application delivery.
• Hands-on experience with AWS, Azure, or GCP, and hybrid/cloud-native deployment models.
• Familiarity with authentication/authorization systems (e.g., Keycloak) and network security.
• Strong communication skills with the ability to lead customer discussions and deployment.
• Comfort navigating between technical and business audiences.
• Experience supporting AI/ML infrastructure or ML lifecycle tools is a plus.