Lead AI Solution Architect - Cloud Azure

Michael Page International Pte Ltd; Singapore; On-site; SGD 180,000 - 300,000; Full time

Job summary

Michael Page International Pte Ltd is seeking an AI Solution Architect to design and deliver end-to-end AI platforms for enterprise-scale needs.

You will translate business goals into robust data pipelines, model deployment, APIs, and system integration across cloud and on-prem environments, working with cross-functional teams.

The role focuses on platform governance, standards, and evaluating tools such as Azure ML, Databricks, and open-source frameworks to drive scalable AI.

Responsibilities

• AI solution design and delivery across data pipelines, model deployment, APIs, and system integration.
• Platform leadership for Agentic AI, Model Garden, and AI Workbench.
• Translate business requirements into secure, compliant technical architectures.
• Integrate AI models into enterprise applications with cross-functional teams.
• Define architectural standards and lead AI innovation pilots.
• Evaluate and recommend AI/ML platforms and tools for enterprise adoption.
• Collaborate with cross-functional stakeholders to align AI initiatives.

Job description

• AI Solution Design & Delivery: Design and implement end-to-end AI solutions including data pipelines, model deployment, APIs, and system integration across cloud and on-premise environments.
• Platform Leadership: Lead AI architecture for platforms such as Agentic AI, Model Garden, and AI Workbench.
• Technical Blueprinting: Translate business requirements into technical architectures, select appropriate tools, and ensure secure, compliant designs aligned with enterprise standards and PDPA regulations.
• System Integration: Integrate AI models into enterprise applications and systems, collaborating with engineering and data teams to operationalize solutions.
• Standards & Innovation: Define architectural standards, lead AI innovation pilots, and stay updated on emerging technologies such as vector databases, AI agents, and orchestration frameworks like LangChain and MCP.
• Platform Evaluation: Assess and recommend AI/ML platforms and tools (Azure ML, AI Foundry, Databricks, AWS SageMaker, open-source toolkits) for enterprise adoption.
• Collaboration & Stakeholder Management: Work closely with cross-functional technical and business teams, managing diverse stakeholders and ensuring alignment on AI initiatives.