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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
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:
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