Data and AI Architect

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.