The enterprise platform for enabling private, secure, and regulation-compliant Gen AI models.

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 in building the most cutting-edge enterprise-level AI systems.

This role will work with the U.S. government clients, so it requires U.S. government security clearance or US citizenship. Our company policy also requires in-office presence in San Francisco or New York office for 2-3 days per week.

Responsibilities

• Engage deeply with customers to understand their infrastructure, goals, and constraints, and lead the design and hands-on deployment to ship 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.
• Work with the DevOps team to manage the Dynamo AI SaaS platform.
• Collaborate across product, engineering, and ML teams to design products and features that enable customers to better protect their AI systems.
• Serve as a trusted expert and build strong relationship with customers.

Qualifications

• Prioritize and execute quickly in a fast-paced environment. High motivated and accountable for customer's success.
• Extensive expertise in Kubernetes, Helm, and containerized application delivery.
• Extensive expertise with at least one of AWS, Azure and GCP.
• 4+ years of experience in solution architecture, DevOps, or cloud engineering roles.
• 2+ years of experience directly working with customers.
• 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.
• Expertise in AI/ML infrastructure or ML pipelines is a plus.