Tech Stack:

• Microsoft Azure

• Microsoft Foundry (formerly Azure AI Foundry)

• Azure OpenAI Service

• Azure AI Search

• Terraform / Azure Bicep

• Azure DevOps

• CI/CD

• Azure Virtual Networks (VNets), Private Endpoints, Private DNS

• Microsoft Entra ID, RBAC, Managed Identities

• Azure Key Vault

• Azure Storage

• Azure Monitor, Log Analytics, Application Insights

• Infrastructure as Code (IaC)

• Message Queues & Asynchronous Communication

Required Qualifications:

• Good understanding of enterprise integration and distributed processing patterns, including integration with workflow and delegation platforms, message queues, asynchronous communication, high-volume data processing and large-scale log ingestion and analysis.
  Strong hands-on experience with Microsoft Azure, particularly in cloud infrastructure provisioning, configuration and maintenance.

• Practical experience with Microsoft Foundry (formerly Azure AI Foundry), Azure OpenAI Service, Azure AI Search, including provisioning, configuration and integration with Azure OpenAI.

• Strong knowledge of Infrastructure as Code (IaC) using Terraform and/or Azure Bicep.

• Hands-on experience with Azure DevOps CI/CD pipelines and automated infrastructure deployments.

• Good understanding of Azure networking concepts and services, including VNets, Private Endpoints, Private DNS and network security.

• Solid knowledge of Azure identity and security, including Microsoft Entra ID, RBAC, Managed Identities and Azure Key Vault.

• Experience with Azure Storage and related cloud services.

• Familiarity with observability solutions such as Azure Monitor, Log Analytics and Application Insights.

• Understanding of the AI application lifecycle, including automated deployments, monitoring, maintenance and operational support.

• Very good command of English, both spoken and written.

Nice to Have:

• Experience supporting production-grade AI/GenAI applications hosted on Microsoft Azure.

• Experience designing secure and scalable cloud environments for AI workloads.

• Familiarity with DevOps/MLOps practices and automation across the AI Software Development Lifecycle.

• Understanding of enterprise-level cloud security, governance and operational best practices.

• Experience working in large-scale digital transformation or financial services environments.

• Experienced in using AI tools in day-to-day workflow.

Project Description:

Scope of Services:

• Design, provision and maintain secure and scalable Microsoft Azure infrastructure for AI-powered applications.

• Build and configure environments based on Microsoft Foundry, Azure OpenAI Service and Azure AI Search.

• Provision and configure Azure OpenAI models and integrate AI services with supporting Azure infrastructure.

• Develop and maintain reusable Infrastructure as Code using Terraform and/or Azure Bicep.

• Design and implement automated infrastructure deployment processes using Azure DevOps CI/CD pipelines.

• Configure Azure networking components, including VNets, Private Endpoints, Private DNS and appropriate network security controls.

• Implement identity, access and secrets management using Microsoft Entra ID, RBAC, Managed Identities and Azure Key Vault.

• Configure storage and supporting Azure services required by AI-enabled applications.

• Establish monitoring and observability using Azure Monitor, Log Analytics and Application Insights.

• Build and maintain scalable integration capabilities for enterprise and AI workloads, including asynchronous processing, messaging, high-throughput data flows and centralised processing of application and infrastructure logs.

• Support integrations with enterprise workflow and delegation platforms, ensuring reliable communication and data processing across distributed systems.

• Support automated deployment, monitoring, troubleshooting and operational maintenance of AI applications.

• Collaborate with software engineering, AI and platform teams to improve the reliability, security and automation of the AI development lifecycle.

• Apply cloud engineering, DevOps and security best practices to ensure environments are maintainable, repeatable, scalable and production-ready.