Associate Principal - Architecture

AI Platform Architect – GPU, Kubernetes & AI Infrastructure Experience: 12- 16 Years Role: AI Platform Architect Domain: AI Infrastructure, Kubernetes, GPU Platforms, MLOps/GenAIOps Employment Type: Full-Time Key Responsibilities Design enterprise AI platforms, GPU-enabled Kubernetes environments, and cloud/on-prem landing zones. Define platform blueprints, site bootstrap automation, Infrastructure-as-Code, and GitOps operating models. Architect multi-tenant AI platforms, tenant onboarding frameworks, and lifecycle management processes. Design AI model serving, inference, training, autoscaling, GPU scheduling, and resource-sharing architectures. Establish MLOps/GenAIOps frameworks including model registry, CI/CD, observability, and FinOps integration. Define HA/DR strategies, cross-region resiliency, failover mechanisms, and recovery workflows. Lead architecture reviews, design workshops, and technical governance across engineering teams. Act as design authority for AI, Kubernetes, and GPU platform architecture decisions. Must-Have Skills Platform & Cloud Architecture 12+ years of IT experience with 5+ years in cloud/platform architecture. Strong experience designing large-scale cloud and hybrid infrastructure platforms. Expertise in landing zones, IAM/KMS, networking, VPC/VNet, hybrid connectivity, and multi-account architectures. Professional cloud certification (AWS/Azure/GCP). Kubernetes & Linux Deep Kubernetes architecture and operational experience (EKS, AKS, GKE, OpenShift, On-Prem K8s). Strong expertise in multi-tenancy, workload isolation, cluster design, and platform operations. Advanced Linux administration, hardening, networking, and troubleshooting (RHEL/CentOS/Ubuntu). 
 
 Infrastructure Automation 
 
 Hands-on experience with Terraform or equivalent Infrastructure-as-Code tools. 
 Strong knowledge of GitOps, automation pipelines, and platform engineering practices. 
 
 AI Platform & GPU Infrastructure 
 
 Experience designing AI training and inference platforms. 
 Knowledge of GPU scheduling, workload orchestration, model serving, and inference scaling. 
 Exposure to multi-tenant AI platform security, quota management, and workload isolation. 
 
 High Availability & Resiliency 
 
 Expertise in HA/DR, multi-region architecture, disaster recovery, failover, and RTO/RPO planning. 
 
 Stakeholder Management 
 
 Strong customer-facing experience conducting architecture workshops and executive design reviews. 
 Ability to translate business requirements into scalable technical solutions. 
 
 Preferred Skills NVIDIA AI Enterprise (NVAIE), NIM, Dynamo, RunAI. GPU sharing technologies (MIG, Fractional GPU). Rafay, Spectro Cloud, vCluster, OPA, Kyverno. SageMaker, Vertex AI, Azure ML. Telco, Edge, 5G MEC, AWS Outposts, Azure Local.