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About the role
This senior role leads the enterprise AI platform architecture for a bank in Singapore, owning the technology stack that supports AI adoption at scale. You will set standards and governance so AI capabilities can be deployed securely and reliably across the organisation. It suits a recognised technical authority with deep experience in distributed systems, data architecture and AI platform engineering in regulated settings.
What you'll do
Define the long-term AI platform strategy, architecture vision and technology roadmap.
Establish enterprise architecture standards, patterns and reusable frameworks for AI platform adoption.
Shape the evolution of the agentic AI ecosystem, covering scalability, resilience, governance and regulatory compliance.
Advise senior executives and technology leadership on strategic AI platform investments and architectural decisions.
Drive technology standardisation while balancing innovation, operational efficiency and risk management.
Act as principal architect for the enterprise AI platform.
Define and govern platform interfaces, service boundaries, data contracts and operational controls.
Lead architecture reviews and design authority forums for AI-related initiatives.
Collaborate with engineering, data, infrastructure, cybersecurity and risk teams to deliver scalable AI services.
Support adoption of AI capabilities across business functions through reusable platform services and reference architectures.
Drive multi-provider AI model strategies that optimise performance, resilience, portability and cost.
Design and govern distributed execution architectures supporting agentic and AI-enabled workloads.
Establish standards for orchestration, durable workflows, agent state management and tool integration.
Define enterprise approaches for model deployment, evaluation, observability, monitoring and lifecycle management.
Create canonical data models and semantic layers across heterogeneous enterprise data domains.
Govern architecture decisions relating to lakehouse platforms, object storage, graph databases, vector stores and NoSQL technologies.
Lead architecture decision record (ADR) development and architecture review board submissions.
Provide technical leadership and mentorship across architecture, engineering and data teams.
Develop architectural capability within the organisation through coaching, standards and knowledge sharing.
Influence technology direction across teams without direct reporting authority.
Foster a culture of engineering excellence, innovation and architectural discipline.
Ensure AI platform architecture aligns with enterprise risk management frameworks.
Embed security, privacy, auditability, explainability and resiliency principles into platform design.
Define controls supporting sovereign deployment requirements and data localisation obligations.
Drive architecture patterns that mitigate operational, technology, cyber and model risks.
Establis
Requirements
15+ years of experience in software engineering, platform architecture, data architecture or distributed systems engineering, with a strong track record of building enterprise-scale platforms.
Proven experience designing and evolving enterprise platforms that support multiple engineering teams and business domains.
Deep expertise in distributed systems, including execution models, state management, consistency, concurrency, resiliency and failure recovery.
Strong experience defining enterprise architecture standards, technology roadmaps and governance frameworks within large, federated organisations.
Expertise in control plane architecture, including identity, authorisation, policy enforcement, routing, auditability and delegated machine-to-machine access controls.
Experience designing canonical data models, ontologies, taxonomies, semantic frameworks, knowledge graphs, RDF models or property graph architectures.
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