Director, AI Architecture

Job Summary

The Director, AI Architecture is accountable for defining and governing the Bank's enterprise AI platform architecture. This role owns the foundational technology stack that enables AI adoption at scale, including the execution substrate, control plane, model serving infrastructure, and underlying data architecture.

The role holder will establish enterprise standards, architectural principles, and governance frameworks that enable secure, scalable, resilient, and compliant deployment of AI capabilities across the Bank. The individual will work across business, technology, data, cybersecurity, risk, and engineering teams to create a reusable AI platform that supports agentic systems, generative AI, machine learning, and future intelligent automation capabilities.

The successful candidate will be a recognized technical authority with deep expertise in distributed systems, data architecture, AI platform engineering, and enterprise governance within highly regulated environments.

Key Responsibilities

Strategy

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 standardization while balancing innovation, operational efficiency, and risk management.

Business

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 optimize performance, resilience, portability, and cost.

Processes

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.

People & Talent

Provide technical leadership and mentorship across architecture, engineering, and data teams.
Develop architectural capability within the organization 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.

Risk Management

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 localization obligations.
Drive architecture patterns that mitigate operational, technology, cyber, and model risks.

Governance

Establish and enforce enterprise-wide architecture standards for AI systems.
Drive governance frameworks covering identity, authorization, tool access, routing, audit, and usage controls.
Partner with Risk, Compliance, Legal, and Information Security teams to ensure regulatory compliance.
Provide evidence and architectural assurance for internal governance and regulatory reviews.

Regulatory & Business Conduct

Display exemplary conduct and live by the Group's Values and Code of Conduct.
Take personal responsibility for embedding the highest standards of ethics, regulatory compliance, and business conduct across Standard Chartered Bank.
Ensure compliance with all applicable laws, regulations, internal policies, and technology governance requirements.
Effectively identify, assess, escalate, mitigate, and resolve risk, conduct, and compliance matters associated with AI platforms and services.

Our Ideal Candidate

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.
Experience architecting large-scale data platforms leveraging lakehouse architectures, object storage, graph databases, vector databases, and NoSQL technologies.
Strong understanding of AI platform engineering, model serving infrastructure, LLM deployment, retrieval architectures, observability, evaluation, and governance.
Experience with agentic systems, orchestration frameworks, durable execution, agent state management, and tool integration patterns.
Experience operating in regu