DevOps Engineer (AI Platform)

Aimlroles; Pune District; Vor Ort; INR 180.000 - 260.000; Vollzeit

Zusammenfassung

Aimlroles in Pune, India, is seeking an experienced DevOps engineer for AI solutions, focusing on CI/CD, IaC, and scalable deployment.

You will implement monitoring, secure networking, and model deployment pipelines across dev, test, and production environments. Candidates should be proficient with Azure DevOps, GitHub Actions, Terraform, Kubernetes, and cloud security.

Qualifikationen

• CI/CD pipelines for AI deployments.
• IaC with Terraform or similar.
• AI platform deployments and MLOps familiarity.

Aufgaben

• Design and implement CI/CD pipelines for AI solutions.
• Automate infrastructure provisioning using Terraform or Bicep.
• Manage AI environment deployments across dev, test, and production.
• Implement monitoring, logging, and observability for AI services.
• Configure secure environment setup, networking, and access controls.
• Manage model deployment pipelines and versioning.
• Ensure scalable and reliable deployment of agents.
• Implement automated rollback and resilience strategies.

Kenntnisse

Azure DevOps

GitHub Actions

Monitoring

Cloud networking

Security

Tools

Terraform

Kubernetes

Application Insights

Prometheus

Jobbeschreibung

Key Responsibilities

• Design and implement CI/CD pipelines for AI solutions.
• Automate infrastructure provisioning using Terraform or Bicep.
• Manage AI environment deployments across dev, test, and production.
• Implement monitoring, logging, and observability for AI services.
• Configure secure environment setup, networking, and access controls.
• Manage model deployment pipelines and versioning.
• Ensure scalable and reliable deployment of agents.
• Implement automated rollback and resilience strategies.

Required Skills

• Azure DevOps / GitHub Actions
• Terraform / Infrastructure as Code
• Kubernetes / containerization
• Monitoring tools (Application Insights, Prometheus, etc.)
• Cloud networking and security

Preferred Experience

• AI platform deployments
• MLOps pipelines
• Model lifecycle management

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