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AI-Infra Network SME
2 months ago
An in-depth hands-on experience in design, document and implement Data Center / Private Cloud Network Infrastructure required to run GPU based AI architectures for Training and Inferencing.
Experienced in Network infra solution design for the heterogeneous environment in hyperscale data centers using NVIDIA InfiniBand / Cisco ACI / Cisco NxOS / Arista based GPU fabric infrastructure.
Understanding of the scalable and non-blocking GPU clusters farm design based on Spine and Leaf architecture.
High speed storage connectivity for Training and Inferencing clusters with multi-tenancy deployment.
Prepare solution design document, HLD, LLD, MoP, SoP.
Solution design for North-south and east-west traffic engineering and layered security.
Interconnect GPU farm with private clouds, public clouds and on-premises DCs.
Extensive experience in conducting solution readiness assessments observing business and technical perspectives.
Experience in conducting periodic reviews of capacity, inventory utilization, TCO analysis, and prepare business case, budget note for new procurement.
Strong knowledge of the NCP-RA design principles and implementation best practices.
Extensive experience in architecting AI Data Center solutions.
Demonstrate the ability to solve complex, multi-system problems.
Quick learning abilities.
Good Service, Process, Tools and KPI Orientation.
Should be willing to explore new learning all time.
Ability to work in a distributed/multicultural Team.
Good Oral/Written Communication and able to interact at CXO level.
Training and skill-set development.
Multi location team coordination.
B.E / B.Tech from reputed Institute.
Preferred:
o NVIDIA certifications on GPU farm design.
o CCIE (R&S / DC).
o Load balancers like F5, Citrix NetScaler etc.
o Microsoft Azure Architect Design AZ301.
8 12 years experience in DC Infrastructure engineering
At least 2 - 4 years designing / deploying GPU based AI farm infrastructure.
Hands-on experience on NVIDIA networking technologies will be an added advantage.
Participated in End-To-End solutioning and implementation
