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About the role
This senior role leads the enterprise AI platform architecture for a bank in Singapore, owning the foundational stack that supports AI adoption at scale. The position works across business, technology, data, cybersecurity, risk, and engineering teams to build a reusable platform for agentic systems, generative AI, machine learning, and intelligent automation. It suits a recognised technical authority with deep expertise in distributed systems, data architecture, AI platform engineering, and governance in highly regulated settings.
What you'll do
Define and drive the bank's 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 bank's agentic AI ecosystem, ensuring 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 the principal architect for the bank's 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 dep
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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