Specialist - System Management

LTM; Chennai District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

LTM is seeking a Senior Engineer Specialist P3 to support AI Datacenter under the Joint GTM capability enhancement track. You will design, deploy and support GPU clusters and AI infra platforms, and optimize AIML workloads.

The role operates at L2 within the System Core Engineering SME L2/L3/L4 tower, with 5 to 8 years of relevant experience, embedded full-time with delivery teams to ensure SLA adherence and knowledge transfer.

Qualifications

• 5 to 8 years of relevant experience.

Responsibilities

• Designs, deploys, supports GPU clusters and AI infra platforms.
• Optimizes AIML workload performance.
• Operates at L2 level within the System Core Engg SME L2 L3 L4 tower with 5 to 8 years of relevant experience.
• Embedded fulltime within delivery teams to build run and scale the sovereign computeAI stack ensuring SLA adherence, documentation and knowledge transfer.
• Collaborates with stakeholders and follows change and incident management processes.
• Contributes to continuous improvement, automation and regulatory compliance readiness across the engagement.

Skills

AI Infra Deployment

Job description

Job Summary

SSenior Engineer Specialist P3 supporting AI Datacenter under the Joint GTM capabilityenhancement track. Designs, deploys, supports GPU clusters and AI infra platforms. Optimizes AIML workload performance. Operates at L2 level within the System Core Engg SME L2 L3 L4 tower with 5 to 8 Years of relevant experience. Embedded fulltime within delivery teams to build run and scale the sovereign computeAI stack ensuring SLA adherence documentation and knowledge transfer. Collaborates closely with and stakeholders follows changeincident management processes and contributes to continuous improvement automation and regulatory DPDPRBICERTIn compliance readiness across the engagement. GPU Cluster Design AI Infra Deployment Support AIML Workload Optimization NVIDIA Platform Expertise CUDA NVIDIA Stack DGX Reference Architectures MIGGPU Partitioning Performance Benchmarking

Responsibilities

• Designs deploys supports GPU clusters and AI infra platforms
• Optimizes AIML workload performance
• Operates at L2 level within the System Core Engg SME L2 L3 L4 tower with 5 to 8 Years of relevant experience
• Embedded fulltime within delivery teams to build run and scale the sovereign computeAI stack ensuring SLA adherence documentation and knowledge transfer
• Collaborates closely with and stakeholders follows changeincident management processes and contributes to continuous improvement automation and regulatory DPDPRBICERTIn compliance readiness across the engagement
• GPU Cluster Design
• AI Infra Deployment Support
• AIML Workload Optimization
• NVIDIA Platform Expertise
• CUDA
• NVIDIA Stack
• DGX Reference Architectures
• MIGGPU Partitioning
• Performance Benchmarking

Qualifications

• 5 to 8 Years of relevant experience

Skills

• AI Infra Deployment

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