DevOps Engineer / Network Engineer

DevOps Engineer / Network Engineer

Minimum Years of Experience:

Key Responsibilities

Linux Expertise:

• Possess in-depth knowledge of Linux operating systems, including CentOS, Ubuntu, and Red Hat, with expertise in shell scripting, package management, and system administration.
• Configure and optimize Linux-based servers for performance, security, and resource utilization, including kernel tuning, file system management, and network configuration.
• Responsible for managing on-premise servers hosting AI/ML workloads, particularly focused on voice agent systems.

On-Premise Infrastructure & GPU Integration:

• Lead the integration of NVIDIA GPUs into on-premise infrastructure for AI/ML training and inference, specifically for voice agent technologies.
• Oversee GPU resource management, ensuring optimal performance, scalability, and reliability of AI applications running on GPU clusters.
• Architect on-premise solutions optimized for AI/ML workloads, ensuring high availability, low latency, and fault tolerance.

Infrastructure as Code (IAC):

• Develop and maintain Infrastructure as Code (IAC) templates using tools like Terraform to define on-premise infrastructure components and GPU clusters for automated provisioning.
• Establish version control practices for IAC templates, ensuring traceability, auditability, and reproducibility of infrastructure changes on-premise.

AI/ML Infrastructure Management:

• Deploy and manage AI/ML applications and voice agents using Docker and Kubernetes in an on-premise environment.
• Ensure efficient scaling, optimization, and high availability of AI workloads, particularly in relation to voice agent applications that operate over the phone.
• Oversee on-premise GPU cluster management for training and inference of voice agents, ensuring smooth, seamless operations and resource scaling.

Voice Agent Project Support:

• Work closely with project teams to implement and optimize AI-driven voice agents deployed over the phone, ensuring the infrastructure meets performance, security, and compliance standards.
• Troubleshoot and optimize the performance of on-premise systems used for voice agent technologies, ensuring robust operation in production environments.

Qualifications

• 5+ years of experience in Infrastructure Management roles, specifically focused on on-premise hardware, GPU integration, and AI/ML applications.
• Strong hands-on experience with operations (DevSecOps) principles, including managing on-premise hardware, networks, and GPUs.
• Proficiency in scripting languages such as Python, PowerShell, or Bash for automation and system configuration.
• Experience in deploying and managing NVIDIA GPU clusters for AI applications, with a focus on on-premise infrastructure.
• Excellent communication and collaboration skills, with the ability to work closely with cross-functional teams and clients.

Certifications such as AWS Solution Architect Associate, Azure Administrator, Certified Kubernetes Administrator, or relevant in