Senior AI Infrastructure Engineer

Job Summary:

We are seeking a highly skilled Senior AI Infrastructure Management Engineer with expertise in Azure, AWS, and AI/ML deployment environments. This role demands deep technical knowledge of Linux, DevOps practices, cloud architecture, and AI/ML operations (MLOps/AIOps). The ideal candidate will be responsible for architecting, deploying, and maintaining scalable and secure infrastructure for enterprise AI applications.

Key Responsibilities:

Linux System Expertise

• Manage and optimize Linux systems (CentOS, Ubuntu, Red Hat)
• Perform kernel tuning, file system configuration, and network optimization
• Develop shell scripts for automation and system management.

Cloud Infrastructure (AWS & Azure)

• Design and implement secure, scalable cloud architectures on AWS and Azure
• Use services like EC2, S3, Lambda, Azure VMs, Blob Storage, and Functions
• Manage hybrid and multi-cloud environments and ensure seamless integration

Infrastructure as Code (IaC)

• Automate infrastructure provisioning using Terraform, CloudFormation, or similar tools
• Maintain infrastructure versioning and ensure traceability of changes
• Enforce DevSecOps best practices and secure configurations

AI/ML Infrastructure Management

• Deploy and manage cloud infrastructure for AI/ML workloads including GPUs
• Scale resources (GPU/CPU) for training and inference workloads
• Deploy AI/ML apps using Docker and Kubernetes
• Ensure high availability, performance, and reliability of AI applications
• Work on MLOps/AIOps pipelines for model deployment and monitoring

Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or related field
• 6+ years of experience in Infrastructure/Cloud/DevOps roles
• Strong experience with AWS, Azure, and Linux systems
• Experience in AI/ML infrastructure setup and management
• Proficient in scripting: Python, Bash, PowerShell
• Hands-on with Kubernetes, Docker, and cloud-native services
• Experience with DevSecOps principles and CI/CD tools

• Certifications (preferred):

• AWS Solution Architect Associate / Cloud Practitioner
• Azure DevOps Engineer / Administrator
• Certified Kubernetes Administrator (CKA)

Preferred Skills:

• Experience with GPU cluster management for AI workloads
• Strong knowledge of cloud security and compliance
• Familiarity with real-time monitoring and logging tools
• Exposure to modern data stacks and AI lifecycle management