AI Solution Architect

Job Overview We are seeking an experienced AI Solution Architect to design and lead end-to-end enterprise AI Factory and GPU infrastructure solutions spanning compute, high-performance networking, storage, Kubernetes, cloud, and AI/ML platforms.

The role requires strong expertise in NVIDIA GPU technologies, AI workloads, scalable infrastructure architecture, security, observability, performance engineering, and capacity planning .

Key Responsibilities

Own end-to-end architecture for AI Factory and enterprise AI solutions from requirements through production readiness. Assess AI/ML workload requirements for training, fine-tuning, inference, batch processing, and high-performance computing.

Design GPU compute architectures including NVIDIA HGX/DGX/OEM platforms, multi-GPU systems, NVLink/NVSwitch, and GPU resource allocation. Design high-performance AI networking using 100/200/400/800G Ethernet, EVPN/VXLAN, and leaf-spine architectures.

Design AI storage and data architectures using object storage, parallel file systems like Ceph, WEKA, , or equivalent platforms. Define AI platform architecture across Kubernetes, HPC, container runtimes, model-serving platforms, and enterprise AI frameworks.

Establish architecture standards for security, identity, tenant isolation, data protection, observability, disaster recovery, and operational resilience. Develop reference architectures, high-level/low-level designs, capacity models, bills of materials, technology evaluations, and implementation roadmaps.

Lead technical evaluations, proof-of-concepts, vendor assessments, and architecture review boards. Collaborate with infrastructure, network, security, storage, cloud, data, application, and operations teams.

Define performance, availability, scalability, security, and cost objectives and validate architecture against measurable acceptance criteria. Provide technical leadership during deployment, migration, integration, troubleshooting, and production transition.

• Required Techni