Data Science Lead - R01572475

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