Cloud Platform Architect

The Cloud Platform team owns the production inferencing service that serves SambaNova's models to customers on RDU accelerators, including capacity planning, deployment, monitoring, and incident response across regions in the United States, Asia, Europe, and Latin America.

The Cloud Operations team is seeking an experienced engineering leader to scale the platform our internal and external customers use to access SambaNova RDUs.

In this role, you'll architecting our next-generation system from the ground up, running the Kubernetes infrastructure that powers some of the most advanced AI workloads in the industry, and bridging multi-cloud and on-prem environments in ways no generic SaaS company can offer. Your work will directly impact the productivity of every engineer at SambaNova and by extension, the speed at which we ship the future of AI computing.

Some of your responsibilities include:

• Architect, build, and maintain our next-generation internal developer platform, automating and streamlining our cloud and on-prem infrastructure
• Design, write, and manage Terraform modules to provision and manage resources across AWS, GCP, and Azure, ensuring consistency and reproducibility
• Build and manage highly available, secure, and performant Kubernetes clusters that serve as the primary runtime for our diverse AI workloads
• Design and implement robust networking solutions (VPCs, load balancers, firewalls, service meshes) that seamlessly connect our multi-cloud and hybrid environments
• Collaborate with AI and software engineering teams to understand their needs, provide golden paths to production, and build internal tools that accelerate their development cycles
• Implement best practices for observability (monitoring, logging, tracing) to ensure system reliability and performance, and participate in on-call rotation

• 7+ years of experience in DevOps, Site Reliability Engineering (SRE), or Cloud Infrastructure roles
• Proficiency in at least one programming language (e.g., Python, Go, Rust)
• Expertise with Kubernetes (EKS, GKE, or self-managed) in production environments - pods, operators, CRDs, CNIs, etc.
• Expertise with Infrastructure as Code with the ability to manage complex, multi-cloud environments
• Strong proficiency with at least one major cloud provider (AWS, GCP, or Azure), with a solid understanding of the core services (compute, storage, networking, IAM)
• Networking fundamentals (TCP/IP, DNS, HTTP, load balancing) and security best practices in the cloud

• Experience in a hybrid environment bridging cloud and on-premise/data center infrastructure
• Experience managing infrastructure for data-intensive or ML/AI workloads
• Knowledge of building and maintaining CI/CD pipelines (e.g., GitLab CI, Jenkins, ArgoCD)
• Experience with service mesh technologies (e.g., Istio, Linkerd)
• Contributions to open-source projects or a public portfolio of code (GitHub)