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Microsoft Corporation Logo Microsoft Corporation · IT - Software Development

Cloud Solution Architect - Apps Innovation

France, Multiple Locations · Job Posted March 22, 2026
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Job Description

We’re looking for a Cloud Solution Architect (CSA) who specializes in data platforms and analytics to help customers build secure, scalable, and AI-ready solutions on Microsoft Azure. In this customer-facing role, you’ll deliver engagements that span architecture design, proof of concepts, and production deployments, ensuring performance, resiliency, and security across mission-critical workloads. As part of the Cloud + AI Data team, you’ll leverage existing Repeatable IP and execution engines with accountability to drive delivery excellence, accelerate adoption, and ensure a successful deployment for the customer for services like Microsoft Fabric, Azure Databricks, Cosmos DB, and Purview. You’ll collaborate with engineering teams, share best practices, and stay current with evolving trends to help customers unlock the full value of their data and AI investments.

Job Responsibility

  • Engage with customer IT and business leaders to understand their data estate, priorities, and success measures, and design secure, scalable Data & AI solutions that deliver measurable business value
  • Lead architecture design sessions, develop Data & Analytics roadmaps, and drive Proof of Concepts (POCs) and Minimum Viable Products (MVPs) to accelerate adoption and ensure long-term technical viability
  • Own the end-to-end technical delivery results, ensuring completeness and accuracy of consumption and customer success plans in collaboration with the CSAM
  • Deliver repeatable intellectual property (IP) to achieve targeted outcomes, accelerate Azure Consumed Revenue (ACR), and contribute to centralized IP development initiatives
  • Provide delivery oversight and escalation support for key Factory engagements across Data & Analytics workloads
  • Drive technical excellence by leading the health, resiliency, security, and optimization of mission-critical data workloads, ensuring readiness for production-scale AI use cases
  • Identify and resolve technical blockers, share customer feedback with engineering teams, and influence product improvements through Voice of the Customer insights
  • Maintain deep technical expertise and stay current with market trends, competitive insights, and Microsoft’s evolving data and AI capabilities
  • Be accredited and certified to deliver with advanced and expert-level proficiency in priority workloads including Microsoft Fabric, Azure Databricks, Microsoft Purview, Azure SQL, PostgreSQL, MySQL, and Cosmos DB
  • Demonstrate a growth mindset by continuously aligning your skills to team and customer needs, contributing to technical communities, and mentoring others to accelerate customer outcomes

Requirements

  • Bachelor's Degree in Computer Science, Information Technology, Engineering, Business, Liberal Arts, or related field AND experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or consulting OR equivalent experience
  • Required Technical Qualifications: Microsoft Foundry: Azure OpenAI Service for deploying GPT models, embeddings, and prompt engineering
  • Azure AI Services for integrating vision, speech, and language capabilities
  • AI Search
  • Azure Machine Learning for model lifecycle management, including:Training, deployment, and monitoring
  • GenAI Ops and its compontents DevOps, DevSecOps, MLOps for CI/CD pipelines and automated retraining
  • LLMOps: Evaluations
  • Red Teaming

Nice to have

  • *Plus to have: Experience in Agent Framework or similar: LangChain, LangGraph, Semanic Kernel, AutoGen, LamaIndex
  • Strong proficiency in Python, Java, C# or Rust
  • Proficiency in application development
  • Application architecture design
  • Microservices design and implementation
  • Design patterns (Gang of 4)
  • Object oriented design
  • Test Driven Development, Domain Driven Design
  • Script implementation using python, bash, powershell etc..
  • Operationalization of AI Solutions: Containerization and deployment using Azure Kubernetes Service (AKS), Conrainer Apps or AppService
  • Scaling AI workloads with Azure Functions, Event Grid, and Logic Apps
  • Implementing model governance, versioning, and rollback strategies
  • Knowledge of specific platforms for GenAIOps implementation: AzureDevOps, Github or similar
  • Data Platforms: Azure Cosmos DB and Azure SQL for AI-driven applications
  • Azure Databricks for feature engineering and ML workflows
  • Strong Understanding: Prompt engineering and optimization for generative AI
  • Responsible AI principles: fairness, transparency, and compliance
  • Security, privacy, and governance for AI workloads
  • OWASP top 10 for AI
  • Performance tuning and cost optimization for large-scale AI deployments
  • OpenAI & Generative AI Expertise: Fine-tuning and managing GPT models for enterprise use cases
  • Building conversational AI, copilots, and intelligent agents
  • Knowledge of embeddings, vector search, and semantic search
  • Basic AI architectures
  • RAG, query rewriting, HyDE, Agentic RAG
  • Agent design patterns
  • Tools usage
  • MCP
  • Multi Agent Architectures like group chat, handoff, magnetic…
  • Familiarity with AI certifications: Microsoft Certified: Azure AI Engineer AssociateAI-900: Azure AI Fundamentals.
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