Funic Tech - Senior Azure Cloud Engineer - AI/ML in Bangalore, भारत

Senior Cloud Engineer - AI/MLExperience : 5 - 8 YearsLocation : BangaloreWork Mode : OnsiteJoining : Immediate to 15 DaysJob Overview :We are looking for an experienced Senior Cloud Engineer - AI/ML with strong hands-on expertise in Azure, Databricks, Kubernetes, AKS, ARO, Terraform, MLflow, CI/CD, and https://jobeax.com/link/dkwYzxUmwjHripsh ideal candidate will be responsible for supporting ML/AI development teams and building scalable, secure, and automated cloud infrastructure and deployment workflows. The role involves driving end-to-end automation for machine learning model deployment, MLOps, infrastructure provisioning, monitoring, and operations across Azure, Databricks, and Kubernetes https://jobeax.com/link/tlplQAnK5B36KMXq Responsibilities :- Design, build, and maintain CI/CD and Continuous Training (CT) pipelines for ML models using Azure DevOps, GitHub Actions, Jenkins, or similar tools.- Develop and manage deployment workflows for Databricks Jobs, MLflow models, APIs, and microservices.- Deploy and operate ML workloads on Azure Kubernetes Service (AKS) and Azure Red Hat OpenShift (ARO).- Automate cloud infrastructure provisioning and configuration using Terraform, Python, Bash, PowerShell, and Infrastructure as Code (IaC) practices.- Implement GitOps-based deployment and infrastructure management wherever applicable.- Manage and optimize Azure Databricks workspaces, clusters, compute resources, and related cloud services.- Configure and maintain AKS/ARO clusters, networking, ingress, storage, secrets, and model-serving environments.- Build scalable and reliable environments for ML model training, deployment, inference, and monitoring.- Implement monitoring, logging, alerting, and observability for cloud and ML workloads.- Troubleshoot infrastructure, deployment, Kubernetes, networking, and application-related issues.- Collaborate closely with ML Engineers, Data Engineers, Data Scientists, DevOps Engineers, and Application Teams.- Implement best practices for cloud security, identity and access management, governance, compliance, and cost optimization.- Support production deployments and ensure high availability, scalability, and reliability of AI/ML workloads.- Continuously improve automation, deployment processes, and operational https://jobeax.com/link/GK6JLJWOsFhSBApv Skills :- 5 - 8 years of experience in Cloud Engineering, DevOps, MLOps, or related roles.- Strong hands-on experience with Microsoft Azure.- Strong experience with Azure Kubernetes Service (AKS).- Experience with Azure Red Hat OpenShift (ARO).- Strong knowledge of Azure Databricks and Databricks deployment/management.- Hands-on experience with MLflow and ML model lifecycle management.- Strong understanding of Kubernetes-based application and model deployments.- Hands-on experience with Terraform / Infrastructure as Code (IaC).- Strong scripting/programming skills in Python.- Good knowledge of Bash and/or PowerShell.- Experience building and managing CI/CD pipelines using Azure DevOps, GitHub Actions, Jenkins, or similar tools.- Understanding of GitOps, containerization, Docker, Kubernetes, and automated deployments.- Good understanding of cloud networking, security, IAM, secrets management, and distributed systems.- Experience with monitoring and observability tools for cloud/Kubernetes https://jobeax.com/link/TcYMIwwXyQaLOZSp Skills :- Experience supporting AI/ML or MLOps platforms in enterprise environments.- Exposure to Generative AI, LLMs, Agentic AI, or RAG pipelines.- Experience deploying and managing AI/ML inference or model-serving workloads.- Knowledge of Azure AI services and cloud-native AI architectures.- Experience with GitOps tools such as Argo CD or Flux.- Knowledge of Prometheus, Grafana, Azure Monitor, Log Analytics, or similar monitoring platforms.- Experience with enterprise governance, security, compliance, and cost optimization. (ref:hirist.tech)