Join Capgemini and empower your career in a collaborative global community. Reimagine possibilities and help leading organizations unlock technology's value for a more sustainable and inclusive world. This role focuses on designing and developing end-to-end AI/ML/Gen AI/Agentic AI solutions for intelligent automation.

As an Azure Cloud Solution Architect, you will leverage your extensive experience in architecting and implementing cloud-native solutions within the Microsoft Azure ecosystem. Your expertise will be crucial in driving innovation and delivering impactful AI-driven automation.

Capgemini is a global leader in business and technology transformation, dedicated to accelerating the digital and sustainable transition for enterprises and society. With a legacy of over 55 years and a diverse team of 340,000 professionals across more than 50 countries, Capgemini delivers end-to-end services powered by AI, cloud, and data expertise, driving tangible results for clients.

Architect scalable, secure, and resilient AI/ML/Gen AI solutions utilizing Azure services such as Azure Machine Learning, Azure OpenAI, Azure Functions, Logic Apps, Azure Synapse Analytics, Azure Databricks, and Azure Kubernetes Service (AKS).

Develop architecture blueprints aligned with the Azure Well-Architected Framework and enterprise standards. Lead the development and deployment of machine learning models using Azure ML pipelines, MLflow, and Python SDKs.

Implement Infrastructure as Code (IaC) with Terraform or Azure Resource Manager (ARM) templates for automated Azure resource provisioning. Integrate AI/ML solutions into Azure architectures using services like Azure Data Factory, Event Grid, Service Bus, and Logic Apps, ensuring seamless data flow.

Design secure and scalable network architectures using Azure Virtual Network, Network Security Groups, Application Gateway, and ExpressRoute. Ensure high availability and disaster recovery strategies for networked solutions.

A Bachelor's or Master's degree in Computer Science, Information Technology, or a related field is required.

Proven experience as a DevOps Engineer, with a strong focus on Azure. In-depth knowledge of Azure services and DevOps best practices is essential. Proficiency in scripting languages like PowerShell or Bash is necessary.

Familiarity with machine learning and Gen AI frameworks and libraries is expected. Expertise in Compute, Storage, Networking, Security, PaaS, Serverless architectures, Azure API Management, and Azure Functions is also required.