About the role
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