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
