Summary: The primary purpose of this role is to take charge of deploying, operating, and supporting AI/GenAI workloads in a production workplace, focusing on utilizing Microsoft Azure and various DevOps practices to ensure operational reliability and efficiency. Main

Responsibilities:
• Independently deploy, operate, and support AI/GenAI workloads in production environments.
• Manage Azure resources, including identity, security, and networking.
• Administer and manage Azure Kubernetes Service (AKS), including all related activities.
• Implement Kubernetes networking and traffic management strategies.
• Implement autoscaling and event-driven scaling solutions.
• Design and implement CI/CD pipelines with a focus on security and integration.
• Conduct monitoring and observability implementations for workloads.
• Establish FinOps practices for cost management and optimization.
• Troubleshoot production issues effectively and independently.




• Own production deployments and ensure operational reliability. Key

Requirements:
• 7-12 years of experience in DevOps or Cloud Engineering.
• Hands-on experience deploying and managing AI workloads.
• Strong expertise in Microsoft Azure and related services.
• Experience with Docker and Azure Kubernetes Service (AKS).
• Proficient in CI/CD pipeline design and implementation.
• Familiarity with monitoring and observability tools.
• Skilled in troubleshooting complex production issues. Nice to Have:
• Experience with FinOps practices.
• Proficiency in AI/LLM observability and evaluation.
• Knowledge of DevSecOps security practices.
• Proficiency in both English and French.
• Knowledge of enterprise-scale project management.

📌 DevOps Senior Engineer/Architect (Bengaluru)
🏢 Emagine
📍 Bengaluru