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.
