5 - 10 years
7 - 17 Lacs
Posted:1 week ago|
Platform:
Work from Office
Full Time
Strong hands-on experience with Azure AI services: Azure OpenAI, Azure Cognitive Services, Azure Machine Learning.
Deep understanding of Cloud Foundry architecture, BOSH, and service broker integration.
Proficiency in Python, .NET, or Java for AI and microservices development.
Experience with containerization (Docker) and orchestration (Kubernetes).
Familiarity with CI/CD tools like Azure DevOps, GitHub Actions, or Jenkins.
Strong knowledge of REST APIs, OAuth2, and secure API integration.
Experience in monitoring and logging using tools like Azure Monitor, App Insights, or Prometheus/Grafana.
Experience with multi-cloud or hybrid cloud environments.
Familiarity with MLOps practices and tools like MLflow or Kubeflow.
Exposure to event-driven architectures using Azure Event Grid, Service Bus, or Kafka.
Knowledge of data engineering pipelines using Azure Data Factory or Synapse.
Understanding of AI governance, model explainability, and responsible AI practices.
Lead the design and implementation of AI-driven solutions using Azure AI services (e.g., Azure OpenAI, Cognitive Services, Azure ML).
Architect and deploy cloud-native applications on Cloud Foundry and integrate them with Azure services.
Collaborate with data scientists, developers, and DevOps teams to operationalize AI models in production environments.
Design and implement CI/CD pipelines for AI and microservices-based applications.
Ensure security, scalability, and performance optimization of deployed solutions.
Provide technical leadership and mentoring to development teams on best practices in AI and cloud-native development.
Troubleshoot and resolve issues related to AI model deployment, API integration, and cloud infrastructure.
Stay updated with the latest trends in Azure AI, Cloud Foundry, and cloud-native technologies.
Tata Consultancy Services
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