We’re seeking a Cloud Solution Architect (CSA) with deep expertise across Azure workloads, including AI, Infrastructure, who is passionate about solving complex challenges and helping enterprise customers accelerate their digital transformation. In this senior, customer-facing role, you’ll lead strategic technical engagements, advise C-level executives, and partner with Customer Success Leaders to shape and execute cloud strategies that drive innovation and business value. You’ll guide customers through architecture design, deployment, and operational excellence, helping them scale AI solutions, modernize applications, and optimize infrastructure on Microsoft Azure. This is an opportunity to make a meaningful impact by enabling customers to realize the full potential of the cloud.
Responsibilities:
- Build trusted relationships with IT Executives and business leaders to shape their Cloud and AI strategy, acting as a technical advisor and champion for their success.
- Identify the business priorities of customer decision-makers to ensure that your activities and recommendations are relevant to their needs.
- Actively promote strategic initiatives that support the success of the customer project while consistently engaging in risk mitigation efforts.
- Lead architectural design sessions and guide the implementation of secure, scalable, and resilient solutions using Microsoft’s best practices and frameworks like CAF and WAF.
Required 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 components DevOps DevSecOps MLOps for CI/CD pipelines and automated retraining.
- LLMOps Evaluations Red Teaming *Plus to have Experience in Agent Framework or similar LangChain, LangGraph, Semanic Kernel, AutoGen, LamaIndex
- Knowledge of specific platforms for GenAIOps implementation: AzureDevOps, Github or similar Data Platforms: Azure Cosmos DB and Azure SQL for AI-driven applications.
- Experience in AI/ML engineering and end-to-end lifecycle managemen
- Experience with Azure AI Services / Azure OpenAI
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