Chief Architect - GPU Orchestration - Cloud Native - Startup - R

Chief ArchitectCloud Native Orchestration Platform - Cloud Native AIStartup (revenue-generating, Series A)Company size : 40REMOTE first cultureSmart, fun, low-ego team cultureCompensation : Base Salary 200k - 300k EquityKey Responsibilities : Extending capabiliti es beyond the current CPU optimization into GPU optimization.Develop capabilities to help customers rapidly set up ML EnvironmentArchitecture & Development : Kubernetes-based ML / AI platform.Leadership & Collaboration : with C-staff, product management, engineering, and design partners.Communication : Create detailed architecture diagrams, documents, and presentations.Focus on the User Experience (K8s users, Infrastructure Admin, MLOps staff, etc).Open Source Community : Stay actively involved with CNCF and related projects.Enterprise-Class Solutions : Drive & deliver solutions for enterprise-class data, ML, AI applications.FinOps & SRE Best Practices : FinOps for cloud financial management, modern SRE practices.Qualifications : Entrepreneurial, Startup Experience10 years infrastructure level software architecture and development.Extensive Experience : Linux, Virtualization platforms (hands-on)AWS, GCP or Azure.Strong experience : Kubernetes-based ML / AI systems (Kubeflow, Kueue, KServe, GPU Operators, DRA, Karpenter)Deep knowledge : ML / AI use cases & customer stories of model development, training, inference, & hardware accelerator usage (CPU, GPU, TPU).Modern cloud-native architectures (scalability, availability, reliability, security, observability).Proven track record of delivering complex distributed systems.Active involvement in open-source communities, particularly CNCF and related projects.Strong leadership and team collaboration skills.Excellent communication skills, both verbal and written.Preferred Qualifications : Knowledge of additional ML / AI frameworks and tools.Experience in DevOps practices and tools.Certification in Kubernetes or related technologies.Awareness of FinOps and SRE best practicesBachelors or Masters degree in Computer Science, Engineering, or related field.