AI Enterprise Architect

About the job

We are seeking an experienced Enterprise AI Architect to lead the design and implementation of enterprise-wide AI architecture for a leading organisation undergoing digital and AI transformation.

This is an opportunity to shape the organisation's AI technology strategy, establish scalable AI platforms and architecture standards, and drive the adoption of Generative AI, agentic AI, and machine learning solutions across business functions, leveraging the Microsoft Azure ecosystem.

Responsibilities

You will define and drive the enterprise AI architecture strategy, designing scalable, secure, and reusable AI platforms and solutions across the organisation. Working closely with business stakeholders, engineering teams, and technology leaders, you will translate business requirements into enterprise-grade AI architectures aligned with technology standards and business objectives.

You will lead the architecture of Generative AI, LLM-powered applications, Retrieval-Augmented Generation (RAG), and agentic AI workflows , leveraging Azure AI services and modern AI orchestration frameworks. You will establish reference architectures, reusable solution patterns, and integration standards to accelerate AI adoption across business functions.

You will also provide architectural oversight across AI platforms, data infrastructure, cloud services, MLOps/LLMOps, security, and governance , ensuring AI solutions are scalable, reliable, cost-efficient, and production-ready.

Requirements

We are looking for an experienced AI Enterprise Architect with a strong technical foundation in cloud architecture, software engineering, data platforms, and enterprise AI solutions.

Strong hands-on experience with the Microsoft Azure ecosystem , including Azure AI Foundry (Microsoft Foundry), Azure OpenAI, Azure AI Search, Azure Machine Learning, and related cloud-native services, is essential.

You should have proven experience designing and delivering enterprise Generative AI and agentic AI solutions , including LLMs, RAG, vector databases, multi-agent orchestration, tool/function calling, and integration with enterprise applications. Familiarity with frameworks such as LangChain, LangGraph, Semantic Kernel, or equivalent technologies will be highly relevant.

Experience with Azure data platforms, API integration, cloud security, identity and access management, CI/CD, and MLOps/LLMOps is important. You should also have a strong understanding of enterprise architecture principles, AI governance, and responsible AI practices.

The successful candidate should combine deep technical architecture expertise with strong stakeholder management capabilities , with the ability to define enterprise AI roadmaps, establish architectural standards, and guide engineering teams in delivering AI solutions at scale.

To apply

Interested candidates, please send your resume to Eliza Ng at [email protected] , quoting the job title. Due to the high volume of applications, only shortlisted candidates will be notified.

L/N 16S8060

R/N R1549515