Senior Cloud Platform Engineer, SambaNova Systems

• 5 + years of experience in DevOps, Site Reliability Engineering (SRE), or Cloud Infrastructure roles
• Deep, hands-on expertise with Kubernetes (EKS, GKE, or self-managed) in production environments. You understand pods, operators, CNIs, and CSI
• Proven mastery of Infrastructure as Code, particularly with Terraform, 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)
• A solid foundation in networking fundamentals (TCP/IP, DNS, HTTP, load balancing) and security best practices in the cloud
• A developer mindset: proficiency in at least one programming language (e.g., Python, Go, Java) to automate tasks and build tools. You understand the SDLC
• A systematic problem-solving approach, combined with strong communication skills and a sense of ownership

Desirable

• Our Cloud Operations team is evolving into a high-velocity Internal Platform Team, and we need a visionary engineer to lead this transformation
• This isn't just about keeping the lights on; it's about building the robust, scalable, and automated foundation that empowers our entire engineering organization to develop, deploy, and scale our groundbreaking AI software stack
• You will be the cornerstone engineer, taking ownership of our core infrastructure
• You'll have the autonomy to design, build, and migrate systems onto a modern, DevOps-centric platform using the best tools for the job. Your work will directly impact the productivity of every engineer at SambaNova
• Lead the Transformation: Architect, build, and maintain our next-generation internal developer platform, automating and streamlining our cloud and on-prem infrastructure
• Master of Infrastructure as Code (IaC): Design, write, and manage Terraform modules to provision and manage resources across AWS, GCP, and Azure, ensuring consistency and reproducibility
• Orchestrate at Scale: Build and manage highly available, secure, and performant Kubernetes clusters that serve as the primary runtime for our diverse AI workloads
• Bridge the Gap: Design and implement robust networking solutions (VPCs, load balancers, firewalls, service meshes) that seamlessly connect our multi-cloud and hybrid environments
• Developer Enablement: 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
• Drive Reliability: Implement best practices for observability (monitoring, logging, tracing) to ensure system reliability and performance, and participate in on-call rotation