CloudOps Engineer (L2)

The Frontline Infrastructure Support Engineer (L2) is responsible for providing advanced technical support, incident resolution, and operational management across enterprise IT infrastructure. The role involves diagnosing and resolving complex infrastructure issues, performing administration activities, implementing changes, supporting problem management, and mentoring L1 engineers while ensuring high service availability and SLA compliance.

Roles & Responsibilities

Infrastructure Administration & Operations

• Administer and maintain Windows, Linux, virtualization, Kubernetes, storage, backup and GPU infrastructure to ensure high availability and operational stability.
• Perform proactive health checks, capacity monitoring, performance tuning, and preventive maintenance activities.

• Investigate, troubleshoot, and resolve Level 2 infrastructure incidents within defined SLAs.
• Perform root cause analysis (RCA) for recurring incidents and coordinate with L3 teams for permanent resolution.
• Review escalations from L1 teams and provide technical guidance during incident resolution.
• Participate in Major Incident Management and support service restoration activities.

• Administer Windows Server environments, including Active Directory, Group Policy, DNS, DHCP, File Services, and Windows services.
• Manage user accounts, organizational units, security groups, permissions, and authentication-related activities.
• Troubleshoot server performance, replication, authentication, and domain-related issues.

• Perform Linux server administration, including user management, package management, service configuration, performance tuning, and security patching.
• Analyze system logs, troubleshoot kernel and OS issues, and optimize server performance.

• Administer Cloud native/VMware/Hyper-V environments, including VM provisioning, snapshots, cloning, migration, and resource optimization.
• Monitor hypervisor performance and troubleshoot virtualization platform issues.

• Administer Kubernetes clusters, including node management, workload deployment, pod lifecycle management, namespace administration, and cluster health monitoring.
• Troubleshoot cluster failures, resource constraints, networking, and orchestration issues.

• Administer enterprise storage systems, LUN provisioning, storage allocation, capacity management, and performance optimization.
• Manage enterprise backup solutions, perform backup validation, restore operations, and troubleshoot backup failures.

• Administer GPU-based infrastructure supporting AI/ML workloads.
• Monitor GPU utilization, troubleshoot hardware/software issues, perform firmware validation, and coordinate hardware replacement activities.

• Diagnose server hardware failures involving CPU, memory, storage, RAID, power supplies, and network interfaces.
• Coordinate hardware replacements with vendors and perform post-maintenance validation.

• Execute approved infrastructure changes following organizational change management processes.
• Participate in Problem Management by identifying recurring issues and implementing preventive actions.

• Develop and maintain technical documentation, SOPs, runbooks, and knowledge articles.
• Mentor L1 engineers and contribute to operational excellence and automation initiatives.
• Support audit, compliance, and governance activities.

BE/B-Tech or equivalent with Computer Science or Electronics & Communication

Relevant Experience

• 4–6 years of hands-on experience in Windows/Linux Administration, Active Directory, VMware/Hyper-V, Kubernetes, Storage & Backup Administration, Network Operations, GPU Infrastructure Administration, Troubleshooting, Incident, Problem Management and Infrastructure Troubleshooting.
• Experience supporting mission – critical production environments with 24 x 7 operations
• 4–6 years of experience in Hardware Support, Change Management, Documentation, ITIL Processes, Vendor Coordination, Automation (PowerShell/Bash/Python), Operational Reporting, and Team Collaboration.
• Preferred Exposure: Experience working with cloud platforms including Microsoft Azure, AWS or Google Cloud Platform, cloud native virtualization platforms, VMware, Nutanix, Kubernetes/Openshift environments, cloud native storage, Enterprise storage like NetApp & HPE etc. Backup Solution like Commvault & Cloud native backup tools, enterprise monitoring tools such as Zabbix, Zoho etc. & ITSM Platform including Manage Engine & Service Now etc. and GPU infrastructure supporting AI/ML workload is preferred