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Brillio

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Architect - R01572475

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Architect

Job requirements

Experience Range: With at least 7 to 10 years of experience in AI, advanced analytics, cloud platforms, and solution architecture, including demonstrated expertise in translating business requirements into scalable, secure, production-ready AI solutions Key Responsibilities:
  • Architect and deliver enterprise AI platforms and advanced analytics solutions that align with business objectives and drive measurable outcomes
  • Translate complex business use cases into scalable AI, analytics, and technology architectures leveraging modern cloud and AI capabilities
  • Design and implement AI solutions utilizing Azure Foundry, Azure AI services, and cloud-native technologies to ensure scalability, security, and production readiness
  • Define architecture patterns and frameworks for Generative AI, machine learning, advanced analytics, and intelligent applications
  • Collaborate with business, data, engineering, and platform teams to drive AI initiatives from ideation through implementation
  • Establish standards and best practices for AI platform engineering, integration, governance, security, and operationalization
  • Evaluate emerging AI platform capabilities and technologies to identify opportunities for improving business outcomes
  • Provide architectural guidance to delivery teams and stakeholders to ensure AI investments are aligned with enterprise priorities
Required Skills:
  • Microsoft Azure AI technologies, including Azure Foundry and Azure AI services
  • Designing scalable, secure, and production-ready AI and analytics solutions
  • Generative AI, machine learning, and advanced analytics architectures
  • Enterprise cloud platforms and data platform engineering
  • API design, integration patterns, and modern AI solution architectures
  • AI governance, security, responsible AI, and operationalization best practices
  • MLOps and AI platform automation
Preferred Skills:
  • Leading enterprise AI transformation and platform modernization initiatives
  • GenAI patterns, including LLM applications, Retrieval-Augmented Generation (RAG), agents, prompt engineering, and AI orchestration
  • Building reusable AI platforms and accelerators for enterprise-scale adoption
  • LLMOps, AI observability, and model lifecycle management
  • Connecting AI platform capabilities to measurable business outcomes
Desired Qualifications:
  • Bachelor's degree in Computer Science, Information Technology, Data Science, or a closely related discipline
  • Microsoft Certified: Azure Solutions Architect Expert
  • Microsoft Certified: Azure AI Engineer Associate

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