Cloud DevOps Engineer AI Monitoring Engineer

Cantellat Software; Chennai District; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Cantellat Software is seeking a Cloud DevOps Engineer focused on AI-enabled monitoring to design, implement and maintain scalable cloud infra and DevOps environments. The role demands hands-on expertise with AWS/Azure/GCP, CI/CD, Kubernetes, IaC, and a strong emphasis on observability and AI-driven anomaly detection. You will automate operations, integrate GenAI workflows, and ensure security and reliability in enterprise-scale deployments.

Qualifications

• 5+ years of experience in Cloud, DevOps, SRE, Platform Engineering, or Infrastructure.
• Proven experience with CI/CD, Kubernetes, IaC, and automation.
• Strong understanding of monitoring, observability, logging, and incident management.
• Practical experience with AI-driven monitoring / AIOps / anomaly detection.

Responsibilities

• Design, implement, and maintain scalable cloud infrastructure and DevOps environments across AWS, Azure, or GCP.
• Build and manage CI/CD pipelines, infrastructure automation, and deployment processes.
• Manage Docker/Kubernetes environments and cloud-native applications.
• Implement and maintain monitoring, observability, logging, and alerting solutions.
• Leverage AI/AIOps capabilities for anomaly detection, predictive monitoring, intelligent alerting, event correlation, and root-cause analysis.
• Automate operational activities, incident response, and remediation using scripting languages.
• Integrate AI/ML and Generative AI/LLM capabilities into DevOps and monitoring workflows where applicable.
• Troubleshoot performance, availability, and infrastructure issues and drive continuous improvement.
• Implement DevSecOps, reliability, security, and cloud optimization best practices.

Skills

Cloud platforms (AWS/Azure/GCP)

CI/CD pipelines

Containers (Docker/Kubernetes)

IaC (Terraform/Ansible/CloudFormation)

Monitoring/Observability tools

Scripting (Python/Bash/PowerShell)

AI/AIOps / GenAI concepts

LLM/Generative AI integration

Version control (Git)

Education

Bachelor's degree in CS/Engineering/IT or related field

Tools

Jenkins

GitLab

GitHub Actions

Azure DevOps

Terraform

Ansible

CloudFormation

Dynatrace

Datadog

Prometheus

Job description

Cloud DevOps Engineer AI Monitoring

Location : Chennai

Roles & Responsibilities

• Design, implement, and maintain scalable cloud infrastructure and DevOps environments across AWS, Azure, or GCP.
• Build and manage CI/CD pipelines, infrastructure automation, and deployment processes.
• Manage Docker/Kubernetes environments and cloud-native applications.
• Implement and maintain monitoring, observability, logging, and alerting solutions.
• Leverage AI/AIOps capabilities for anomaly detection, predictive monitoring, intelligent alerting, event correlation, and root-cause analysis.
• Automate operational activities, incident response, and remediation using Python, Bash, or similar scripting languages.
• Integrate AI/ML and Generative AI/LLM capabilities into DevOps and monitoring workflows where applicable.
• Troubleshoot performance, availability, and infrastructure issues and drive continuous improvement.
• Implement DevSecOps, reliability, security, and cloud optimization best practices.

Skills

• Cloud: AWS / Azure / GCP
• DevOps: CI/CD, Jenkins / GitLab / GitHub Actions / Azure DevOps
• Containers: Docker, Kubernetes
• IaC: Terraform / Ansible / CloudFormation
• Monitoring & Observability: Dynatrace / Datadog / Splunk / Prometheus / Grafana / ELK / OpenTelemetry
• Scripting: Python / Bash / PowerShell
• AI/AIOps: AIOps, anomaly detection, predictive analytics, intelligent event management
• GenAI: LLMs, AI APIs, RAG, AI-assisted incident management is an advantage
• Version Control: Git

Requirements

• 5+ years of experience in Cloud, DevOps, SRE, Platform Engineering, or Infrastructure.
• Strong hands-on experience with at least one major cloud platform.
• Proven experience with CI/CD, Kubernetes, Infrastructure as Code, and automation.
• Strong understanding of monitoring, observability, logging, and incident management.
• Practical experience with AI-driven monitoring / AIOps / anomaly detection.
• Strong scripting and troubleshooting skills.
• Experience working in enterprise-scale production environments.
• Good understanding of DevSecOps, reliability, performance, and cloud security.
• Bachelor's degree in Computer Science, Engineering, IT, or a related field preferred.