Infrastructure Solutions Architect
4 weeks ago
About the Role We are looking for aSystems or Solutions Architectwith deep expertise innetworking, infrastructure-as-a-service (IaaS), and cloud-scale system designto help architect and optimizeAI/ML infrastructure . The ideal candidate combines strong fundamentals incloud architecture (AWS or equivalent) ,networking ,compute , andstorage , with hands-on experience inKubernetes, observability, and automation . You’ll design scalable systems that support large AI workloads — enabling efficient training, inference, and data pipelines across distributed environments.Key Responsibilities Architect and scale AI/ML infrastructureacross public cloud (AWS / Azure / GCP) and hybrid environments. Design and optimize compute, storage, and network topologiesfor distributed training and inference clusters. Build and managecontainerized environmentsusingKubernetes, Docker, and Helm . Developautomation frameworksfor provisioning, scaling, and monitoring infrastructure usingPython, Go, and IaC (Terraform / CloudFormation) . Partner with data science and ML Ops teams to alignAI infrastructure requirements(GPU/CPU scaling, caching, throughput, latency). Implementobservability, logging, and tracingusingPrometheus, Grafana, CloudWatch, or Open Telemetry . Drivenetworking automation(BGP, routing, load balancing, VPNs, service meshes) using software-defined networking (SDN) and modern APIs. Lead performance, reliability, and cost-optimization efforts for AI training and inference pipelines. Collaborate cross-functionally with product, platform, and operations teams to ensuresecure, performant, and resilient infrastructure .Required Qualifications Knowledge ofAI/ML infrastructure patterns , including distributed training, inference pipelines, and GPU orchestration. Bachelor’s or Master’s degreein Computer Science, Information Technology, or related field. 10+ years of experiencein systems, infrastructure, or solutions architecture roles. Deep understanding of: Cloud architecture:AWS (preferred), Azure, or GCP Networking:VPC, Transit Gateway, DNS, routing, peering, load balancing, VPN Compute and storage:EC2, ECS/EKS, S3, EBS, EFS, FSx, caching systems Core infrastructure:virtualization, containers, distributed systems, and OS-level tuning Proficiency in Linux systems engineeringandscripting with Python and Bash . Experience with Kubernetes(EKS/GKE/AKS) for large-scale workload orchestration. Experience with Go (Golang)for infrastructure or network automation. Familiarity withInfrastructure-as-Code (IaC)tools like Terraform, Ansible, or CloudFormation. Experience implementingmonitoring and observability systems(Prometheus, Grafana, ELK, Datadog, CloudWatch).Preferred Qualifications Experience withDevOps and MLOps ecosystems(SageMaker, Kubeflow, MLflow, Airflow). AWS or cloud certifications such asSolutions Architect ProfessionalorAdvanced Networking Specialty . Experience inperformance benchmarking ,security hardening , andcost optimizationfor compute-intensive workloads. Strong collaboration skills and ability to communicate complex infrastructure concepts clearly.
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