Data and AI Architect

Roles & Responsibilities

We are partnered with an established premier financial institution in Singapore looking to appoint an Enterprise Data & AI Architect to drive the future state of their intelligence ecosystem. This role sits at the group architecture level, setting the overarching blueprints and design standards that transform how enterprise-wide data and artificial intelligence are architected, governed, and operationalised.

Key Responsibilities:

• Shape and steer the group-wide target-state blueprints and multi-year roadmaps across Lakehouse/Mesh platforms, streaming architectures, and end-to-end MLOps/LLMOps environments.

• Act as the cross-domain design authority, arbitrating architecture review boards, governing design dispensations, and ensuring complex cross-functional programs align with long-term technology roadmaps.

• Publish and enforce robust architecture patterns and reference models covering distributed data modelling, real-time eventing, feature stores, model risk management, and Responsible AI frameworks.

• Work hand-in-hand with business unit Solution Architects and Engineering leads to quality-assure solution designs across batch/real-time streaming pipelines, API scoring, and enterprise retrieval architectures.

• Ensure strict architectural alignment with data privacy, lineage, operational resilience, and financial regulatory risk controls.

Requirements:

• At least 10 years of experience across enterprise or solution architecture, with at least 6 years spent spearheading modern data and AI/ML architectures at enterprise scale.

• Demonstrated background designing and modernising data platforms across hybrid/multi-cloud setups (covering AWS, Azure, or GCP stacks, Kafka, and data lake/lakehouse implementations).

• Deep understanding of enterprise governance, data lineage/metadata, Model Risk Management (MRM), and security/privacy-by-design principles.

Proven track record serving as an architecture design authority, leading architectural governance councils, and influencing senior business and technology stakeholders.

Tell employers what skills you have

Enterprise Search
real-time applications
Architectural Patterns
Pipeline Management
Risk Modeling
Responsible AI
Feature Store
Cross Functional Project Management
Adaptive Streaming
Data Lineage
Business Resilience
Risk and Regulatory
API
Institutional Review Board
Ensuring Design
roadmap strategies