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Metro Bangalore, mid-level 7–9 years, and broad MLOps/Data/DevOps skillset increases competition.
Core data engineering skills transferable, but Azure Foundry and MLOps specialization increase domain-specific sensitivity.
Explicit 7–9 years plus mandatory Azure Foundry, Snowflake, Kubernetes, Terraform and CI/CD makes filters strict.
Design, develop, and maintain backend services and cloud-native applications using microservices architecture on Azure Cloud.
Build and automate CI/CD pipelines for application code and AI Foundry models/agents, including infrastructure provisioning via Terraform.
Manage Azure Foundry deployments, containerized workloads on Kubernetes (AKS), and implement monitoring and operational support for production systems.
7–9 years of combined DevOps and software development experience.
Bachelor’s degree in Computer Science, Engineering, or related discipline (or equivalent hands-on experience).
Expertise in Azure Cloud and Azure AI Foundry, Kubernetes, Terraform, CI/CD automation with GitHub Actions, microservices development in Java/Python/Node.js, and Snowflake SQL.
Experience with containerized deployments, REST API design, observability tools (Prometheus, Grafana, ELK), and secure development practices including Azure Key Vault.
Proven ability to handle end-to-end cloud-native application lifecycle with strong focus on scalability, reliability, and automation in Azure environments.
Experience working with AI model deployments and operational workflows within Azure AI Foundry platform.
Comfortable operating across multiple frameworks and languages in a microservices, containerized, and Git-based release governance context.