Principal AI Infrastructure Architect

Nava; Bengaluru; On-site; INR 5,000,000 - 12,000,000; Full time

Job summary

Nava is seeking a Principal Architect to design and deploy scalable GPU infrastructure across compute, network, storage, and management planes in Bengaluru. This senior IC role focuses on end‑to‑end AI infrastructure integration, defining reference architectures and capacity models while shaping standards for performance and resiliency.

You will work closely with deployment and SRE teams to translate AI workloads into practical, implementable designs and drive improvements based on field results

Qualifications

• 7–12 years designing production cloud, HPC or high‑performance distributed infrastructure.
• Deep tech strength in at least two areas: GPU systems, data center networking, distributed storage or Linux infra.
• Working grasp of NVIDIA architectures, GPU interconnects and data center constraints.
• Ability to produce implementable low‑level designs and capacity/performance models.
• Evidence of architecture decisions deployed and operated in production.

Responsibilities

• Create reference architectures and low-level designs spanning NVIDIA GPU topologies, high‑speed fabrics, storage and management planes.
• Translate AI workload and scale targets into network bandwidth, storage IOPS/throughput, rack count, power and cooling envelopes.
• Define topology, failure domains, resilience patterns and expansion strategy.
• Evaluate trade-offs among NVLink/NVSwitch, InfiniBand/RoCE, parallel storage and orchestration options.
• Define engineering standards, bill‑of‑materials inputs, performance acceptance tests and design review gates.
• Validate designs with deployment and SRE teams; drive improvements from field results and benchmark evidence.

Skills

GPU systems

Data center networking

Distributed storage

Linux infra

Capacity modeling

Job description

About Nava

Nava is a neocloud company purpose-built for the AI era. We design, deploy, and operate large-scale GPU infrastructure and deliver inference-as-a-service to teams building the next generation of AI products. Our platform runs on NVIDIA GPU systems, high-performance RDMA fabrics, and a fully automated, software-defined operations model. Every engineer at Nava works close to the metal, on infrastructure built to keep GPUs saturated and models serving.

About Nava

Nava is a neocloud company purpose-built for the AI era. We design, deploy, and operate large-scale GPU infrastructure and deliver inference-as-a-service to teams building the next generation of AI products. Our platform runs on NVIDIA GPU systems, high-performance RDMA fabrics, and a fully automated, software-defined operations model. Every engineer at Nava works close to the metal, on infrastructure built to keep GPUs saturated and models serving.

About The Role

This is a principal individual-contributor role on the Architecture function. You architect coherent, deployable GPU cluster designs across compute, network, storage, management and physical infrastructure constraints. Architect end-to-end AI infrastructure integrating GPU compute, high-performance networking, distributed storage, and management systems. Define reference architectures, capacity models, performance standards, resiliency requirements, and scalable cluster deployment designs.

What You'll Do

• Create reference architectures and low-level designs spanning NVIDIA GPU topologies, high-speed fabrics, storage and management planes.
• Translate AI workload and scale targets into network bandwidth, storage IOPS/throughput, rack count, power and cooling envelopes.
• Define topology, failure domains, resilience patterns, lifecycle constraints and expansion strategy.
• Evaluate trade-offs among NVLink/NVSwitch, InfiniBand/RoCE, parallel storage and orchestration options.
• Define engineering standards, bill-of-material inputs, performance acceptance tests and design review gates.
• Validate designs with deployment and SRE teams; drive improvements from field results and benchmark evidence.

What You'll Need

• 7-12 years designing production cloud, HPC or high-performance distributed infrastructure.
• Deep technical strength in at least two of GPU systems, data center networking, distributed storage or Linux infrastructure.
• Working grasp of NVIDIA architectures, GPU communication, network fabrics and data center constraints.
• Ability to produce implementable low-level designs and capacity/performance models.
• Evidence of architecture decisions deployed and operated in production.
• Within that, hands-on GPU/AI-datacenter exposure is what we weigh most - we value demonstrated depth over years, as the field is still emerging.

Skills: infrastructure,design,data center,storage