AI & Automation Engineer – Data Center Infrastructure

Location: Noida

Position Overview (Job Summary)

The AI & Automation Engineer will be responsible for modernizing and automating Data Center and Infrastructure operations through Infrastructure-as-Code (IaC), AI-driven automation, and self-service solutions. The role focuses on reducing manual effort, improving operational efficiency, enhancing infrastructure reliability, and enabling intelligent operations across Compute, Storage, Backup, Networking, Azure Local, Hybrid Cloud, and Data Center platforms.

Primary Skills

Automation & Infrastructure as Code

- PowerShell
- Python
- Bash
- Ansible / Red Hat Ansible
- Terraform
- REST APIs
- Git
- CI/CD Pipelines

Cloud & Infrastructure
- Microsoft Azure
- Azure Local
- Hybrid Cloud
- Windows Server
- Linux
- Virtualization
- Storage Platforms
- Backup Solutions
- Networking

AI & Intelligent Automation
- Microsoft Copilot
- Copilot Studio
- AI Agents
- LLM-based Automation Solutions
- API Integrations
- Machine Learning Fundamentals

Secondary Skills
- Azure Monitor
- OpsRamp
- ServiceNow
- Azure DevOps
- Infrastructure Monitoring
- Capacity Planning
- Observability Dashboards
- Disaster Recovery Testing
- Compliance Verification
- FinOps
- Cloud Cost Optimization
- ITSM Processes

Experience
- 5+ years of experience in:
- Data Center Engineering
- Infrastructure Engineering
- Cloud Platforms
- Automation Engineering
- Experience with enterprise-scale infrastructure automation.
- Experience supporting large production environments.
- Robust Infrastructure-as-Code (IaC) implementation experience.
- Experience with AI-driven operational solutions is preferred.

Role and Responsibilities A. Infrastructure Automation




- Design and implement Infrastructure-as-Code solutions.
- Automate provisioning, configuration, patching, and lifecycle management.
- Develop automation frameworks using PowerShell, Python, Terraform, and Ansible.
- Create reusable templates and automation standards.
- Standardize infrastructure deployments globally.

B. AI-Driven Operations
- Develop AI-powered automation workflows.
- Implement self-healing infrastructure capabilities.
- Build predictive analytics solutions for capacity and health monitoring.
- Create AI agents and Copilot-based operational assistants.
- Reduce L1/L2 operational workload through intelligent automation.

C. Data Center Engineering
- Support:
- Compute
- Virtualization
- Storage
- Backup
- Networking
- Hybrid Cloud
- Azure Local
- Automate:
- Capacity Reporting
- Infrastructure Monitoring
- Backup Validation
- DR Testing
- Server Provisioning
- Storage Administration
- Compliance Verification

D. Monitoring & Observability
- Enhance infrastructure visibility through monitoring tools.
- Build automated incident response workflows.
- Correlate events across infrastructure domains.
- Create observability dashboards and KPIs.
- Develop reporting and trend analysis solutions.

E. Service Improvement
- Identify repetitive tasks for automation.
- Build self-service infrastructure capabilities.
- Track automation success metrics:
- Hours saved
- Reduced incidents
- SLA improvement
- Reduced operational costs
- Faster service delivery

F. Security & Governance
- Ensure compliance with security standards.
- Implement least-privilege access controls.
- Support governance and audit requirements.
- Maintain documentation and change management processes.

📌 AI & Automation Engineer (Noida)
🏢 HCLTech
📍 Noida