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Mid-level metro DevOps/MLOps with a generalist title and broad skillset raises candidate competition.
Specialized MLOps and AI infrastructure needs make background fit highly industry-specific.
Explicit 3–5 years and mandatory AWS/Terraform/Kubernetes/MLOps skills make shortlisting strict.
Develop, automate, and maintain AWS-based cloud and AI/ML infrastructure components using Infrastructure as Code (Terraform, CloudFormation) and CI/CD pipelines.
Implement AI-driven observability, self-healing solutions, and disaster recovery strategies to maintain high system uptime, model availability, and proactive incident management.
Manage end-to-end deployment processes for AI/ML models and cloud services, continuously improving automation to reduce operational overhead.
3 to 5 years of experience in DevOps or MLOps roles, preferably in large-scale enterprise environments.
Proficiency in AWS services including disaster recovery tools (AWS Backup, Elastic Disaster Recovery, Lambda).
Strong skills with Infrastructure as Code tools (Terraform, CloudFormation), container orchestration (Docker, Kubernetes, ECS, EKS), and scripting (Python, Shell, PowerShell).
Work Experience Required: 3 to 5 years, AWS Certifications preferred but not mandatory; Location: Chennai, India.
Experienced in building and scaling highly-available AI/ML infrastructure and deployments on AWS with observable, automated operational workflows.
Comfortable working with monitoring and AIOps tools (DataDog, Grafana, Nagios) and integrating AI-assisted developer tools for productivity.
Skilled in handling complex infrastructure automation tasks, disaster recovery designs, and enhancing CI/CD pipelines in a cloud-native enterprise environment.