Senior Director, AI Data Platforms & Knowledge Systems

Page Executive; Singapore; Remote; SGD 120,000 - 180,000; Full time

Job summary

Page Executive is seeking a senior AI Data Strategy & Architecture leader to shape enterprise-wide AI data frameworks, roadmaps and reusable data products. You will advance AI-ready architectures, govern data quality, and evaluate emerging AI tech across diverse markets.

The role requires extensive experience in enterprise data engineering and AI platforms, with a track record of delivering data and AI transformation in complex organisations. International exposure is valued.

Qualifications

• Experience designing enterprise data platforms and AI data architectures.
• Proven track record delivering data and AI transformation initiatives.
• Experience operating in complex, matrixed organisations.
• Knowledge of LLMs, RAG, vector databases and semantic tooling.

Responsibilities

• Shape enterprise AI data frameworks and platform roadmaps.
• Develop reusable data products, semantic assets and data services.
• Advance AI-ready data architectures for scalable AI applications.
• Evaluate emerging technologies across data and AI ecosystems.
• Establish governance, data quality, lineage and metadata standards.

Skills

Data Engineering

Knowledge Graphs

Semantic Technologies

LLMs

RAG

Vector Databases

Data Governance

Metadata Management

AI Platforms

Education

Bachelors in CS/Data Eng

Job description

• Build the Data Foundation for Enterprise AI
• Work Across Emerging AI Technologies

About Our Client

A large-scale international technology and digital services organisation is accelerating the adoption of Artificial Intelligence across its operations. Significant investments are being made in modern data platforms, intelligent automation and AI technologies to enable scalable innovation and business transformation across multiple markets and business domain

Job Description

AI Data Strategy & Architecture

• Shape enterprise-wide AI data frameworks and platform roadmaps.
• Develop reusable data products, semantic assets and data services.
• Advance AI-ready data architectures that enable scalable AI applications.
• Evaluate emerging technologies and evolving approaches across data and AI ecosystems.

Data Platforms & Knowledge Systems

• Expand enterprise data product capabilities that can be leveraged across diverse business functions.
• Develop semantic models, taxonomies and knowledge frameworks that improve AI context and information access.
• Enhance discoverability, scalability and governance of enterprise data assets.

Context Engineering & Retrieval

• Develop retrieval frameworks and context management capabilities for AI and intelligent agent applications.
• Establish approaches covering RAG, vector search, embeddings, knowledge retrieval and contextual reasoning.
• Create reusable patterns that improve AI quality, accuracy and reliability.

Engineering & Platform Excellence

• Review data architectures, pipelines, retrieval frameworks and AI data products to maintain production-grade standards.
• Improve data quality, reliability, performance and operational scalability.
• Enhance observability, lifecycle management and platform resilience.

Governance, Privacy

• Establish standards covering data quality, lineage, metadata and governance.
• Align AI data assets with privacy, security and regulatory requirements.
• Promote secured and sustainable AI practices across enterprise environments.

Innovation & Portfolio Planning

• Assess new technologies and emerging trends across AI and data ecosystems.
• Prioritise initiatives based on business impact, scalability and implementation considerations.
• Contribute to technology planning and capability expansion activities.

The Successful Applicant

Experience

• Degree qualification in Computer Science, Data Engineering, Information Systems, Mathematics or a related discipline.
• Extensive experience in enterprise data engineering, AI platforms, data architecture or data environments.
• Experience building large-scale data platforms and reusable data products.
• Experience operating within complex and highly matrixed organisations.
• Track record of delivering business outcomes through data and AI transformation initiatives.

Technical Expertise

Experience across several of the following domains:

• Data Engineering
• Data Products
• AI Data Platforms
• Knowledge Graphs
• Semantic Technologies
• Metadata Management
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Vector Databases
• Context Engineering
• Cloud Data PlatformsData Governance
• AI Infrastructure

Additional Advantage

• Experience building AI-ready data ecosystems.
• Exposure to enterprise Generative AI initiatives.
• Experience with knowledge management and semantic technologies.
• International or multi-market experience.
• Exposure to large-scale transformation programmes.

What’s on Offer

Broad visibility across technology, data and business functions.

Opportunity to influence the evolution of enterprise AI and data capabilities.

Regular interaction with senior stakeholders across multiple domains.

Exposure to complex, large-scale technology environments.