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