• US Citizen

• Green Card

• EAD (OPT/CPT/GC/H4)

• H1B Work Permit

• Corp-Corp

• W2-Permanent

• W2-Contract

• Contract to Hire

• Consulting/Contract

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 26th Sep 2025

1.    Architecture Design:
o    Deep understanding of comprehensive datacenter architecture plans that align with business goals and technical requirements.
o    Deep understanding of scalable, secure, and efficient datacenter infrastructures.
o    Good knowledge in high availability and disaster recovery capabilities.
2.    Physical Build and Deployment:
o    Understanding of physical build and deployment of datacenter infrastructure, including servers, storage, networking, and virtualization.
o    Understanding of installation, configuration, and maintenance of datacenter hardware and software.
3.    Logical Build and Deployment:
o    Deep understanding in design and implementation of logical datacenter architectures using tools such as Azure DevOps.
o    Good understanding and working knowledge in CI/CD pipelines for automated deployment and configuration.
o    Good understanding in seamless integration of various components and services within the datacenter.
4.    Automation:
o    Ability to strategize and implement automation to streamline datacenter operations.
o    Good understanding in tools such as Ansible, Puppet, or Chef for configuration management and automation.
o    Ability to think through scenarios for scripts and automation workflows to reduce manual intervention and improve efficiency.
5.    AI Solutions:
o    Good understanding to Integrate AI and machine learning solutions to enhance datacenter performance and reliability.
o    Good understanding around predictive analytics models to foresee and mitigate potential issues.
o    Good knowledge in AI-driven monitoring and management tools to optimize resource utilization.
6.    SILICON Area:
o    Good knowledge in designing and managing high-performance computing (HPC) environments tailored for AI and machine learning workloads.
o    Knowledge in datacenter infrastructure for specialized hardware such as GPUs, TPUs, and FPGAs.
o    Knowledge in efficient cooling and power management for high-density compute environments.
7.    AI Datacenters:
o    Knowledge in datacenters specifically for AI workloads, focusing on data throughput, latency, and scalability.
o    Knowledge in AI-driven optimization techniques for resource allocation and workload management.
o    Ability to collaborate with AI research and development teams to support cutting-edge AI applications and services.