Cloud Solution Architect - Cloud & AI Infrastructure

Microsoft Microsoft · Big Tech · Jakarta, Jakarta, ID · Cloud Solution Architecture

This role focuses on helping customers migrate, modernize, and secure their infrastructure on Microsoft Azure, specifically to lay the foundation for scalable, production-ready AI solutions. The Cloud Solution Architect will design and implement scalable solutions, resolve blockers, and accelerate adoption of Azure services, ensuring customer environments are optimized for AI use cases. While the role supports AI, its core craft is cloud infrastructure architecture and migration, not direct AI/ML model development or research.

What you'd actually do

  1. Create business value by translating customer challenges into actionable solutions aligned to high ROI customer outcomes. Ensure a seamless, connected experience that fosters satisfaction, loyalty, and long-term value.
  2. Lead architectural design sessions and deliver secure, scalable, and resilient infrastructure solutions aligned to customer business goals using frameworks like CAF and WAF.
  3. Partner with technical and sales teams to identify opportunities and develop tailored solutions to drive expansion and business value realization.
  4. Drive migration and modernization initiatives, including committed proof of concept and production milestones, across infrastructure, data, SAP, and AI workloads.
  5. Ensure customer environments are optimized for health, resiliency, security, and performance—enabling production-scale AI use cases.

Skills

Required

  • 7+ years experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or consulting OR equivalent experience.
  • Demonstrated experience working in a external customer-facing role.
  • Demonstrated experience working on technical projects.

Nice to have

  • Technical Certification in Cloud is preferred (e.g., Azure, Amazon Web Services, Google, security certifications).

What the JD emphasized

  • production-scale AI use cases
  • AI workloads