Head of Enterprise AI

Page Executive; Singapore; Remote; SGD 150,000 - 230,000; Full time

Job summary

Page Executive is seeking a senior leader in Singapore to shape enterprise AI capabilities and build scalable AI platforms. You will drive architecture, frameworks, and standards across AI engineering teams, with a focus on governance, security and business outcomes.

You will lead the adoption of Generative AI, LLMs and agentic AI across the organisation, evaluating technologies and partnering with senior stakeholders to translate AI into measurable value.

Qualifications

• Requires degree in a technical field and extensive AI/ML experience.
• Experience translating AI tech into measurable business outcomes.
• Exposure to enterprise-scale AI programs and platform development.
• Ability to navigate complex, matrixed organisations.

Responsibilities

• Shape the roadmap for enterprise AI capabilities and services.
• Develop reusable frameworks, reference architectures and engineering standards.
• Evaluate AI technologies, platform components and ecosystem opportunities.
• Advance scalable and secure AI infrastructure across the organisation.
• Build high-performing AI engineering teams and strengthen technical capabilities.
• Foster knowledge, innovation and continuous capability growth.
• Develop enterprise-grade AI agent frameworks and governance practices.
• Convert business opportunities into AI-enabled products and services.
• Establish AI lifecycle practices across MLOps/LLMOps and governance.

Skills

AI Platform Engineering

Machine Learning

Data Science

Generative AI

LLMs

MLOps

Education

Bachelor's degree in Computer Science/AI/Engineering/Math/Statistics

Tools

Cloud Platforms

Big Data Tools

Job description

• Shape Enterprise AI at Scale
• Drive Next-Generation AI Adoption

About Our Client

An organisation operating in the technology and telecoms industry.

Job Description

AI Platforms & Architecture

• Shape the roadmap for enterprise AI capabilities and services.
• Develop reusable frameworks, reference architectures and engineering standards.
• Evaluate AI technologies, platform components and ecosystem opportunities.
• Advance scalable and secure AI infrastructure across the organisation.

Engineering Capability Development

• Build high-performing teams across AI engineering, machine learning and applied AI disciplines.
• Strengthen technical capabilities covering machine learning, Generative AI, optimisation and intelligent systems.
• Foster knowledge, innovation and continuous capability growth.

Generative AI & Agentic AI

• Develop enterprise-grade AI agent frameworks and orchestration models.
• Establish approaches covering RAG, prompt optimisation, evaluation methodologies and governance practices.
• Enhance scalability, reliability and operational effectiveness across AI solutions.

AI Products & Services

• Convert business opportunities into practical AI-enabled products and services.
• Expand AI usage across operational processes, customer journeys and business functions.
• Increase adoption through scalable product design and delivery models.

AI Operations & Governance

• Establish AI lifecycle practices across MLOps, LLMOps and AgentOps.
• Define approaches covering deployment, monitoring, evaluation and optimisation.
• Align AI activities with security, compliance, privacy and governance expectations.

Portfolio & Innovation

• Assess emerging technologies, market developments and innovation opportunities.
• Prioritise initiatives based on business impact, scalability and implementation feasibility.
• Guide technology selection, capability planning and investment allocation discussions

The Successful Applicant

Experience

• Degree qualification in Computer Science, Artificial Intelligence, Engineering, Mathematics, Statistics or a related field.
• Extensive experience within AI, machine learning, data science or AI engineering environments.
• Exposure to enterprise-scale AI programmes and platform development initiatives.
• Experience operating within complex and highly matrixed organisations.
• Track record of translating AI technologies into measurable business outcomes.

Technical Expertise

Experience across several of the following domains:

• Machine Learning
• Deep Learning
• Large Language Models (LLMs)
• Generative AI
• Agentic AI
• Retrieval-Augmented Generation (RAG)
• AI Platform Engineering
• Cloud-based AI Infrastructure
• MLOps / LLMOps
• Data & Platforms

Additional Advantage

• Enterprise Generative AI deployment experience.
• Exposure to large-scale transformation programmes.
• Experience scaling AI solutions from experimentation through operational deployment.
• International or multi-market experience.

What’s on Offer

Significant visibility across technology, data and business functions.

Broad influence on future AI platform and product development.

Close interaction with senior stakeholders across the organisation.

Opportunity to contribute to the evolution of enterprise AI capabilities at scale.