Solution Architect - AI & Data

About the role

A permanent, mid/senior level Solution Architect position in Singapore, focused on enterprise architecture with a strong background in AI and/or data. The role defines and shapes technology architecture, turning complex business requirements into scalable, secure and future-ready solutions, and works closely with business stakeholders, engineering teams, data specialists and senior technology leadership.

Key responsibilities

• Define and develop end-to-end solution architectures aligned with enterprise technology strategy and business objectives.
• Apply TOGAF principles and frameworks to support enterprise architecture governance and solution design.
• Design scalable, secure and resilient architectures across cloud, data and AI environments.
• Translate business requirements into technical architecture, solution blueprints and implementation roadmaps.
• Lead architecture discussions and give technical direction to engineering, infrastructure, data and application teams.
• Evaluate emerging technologies, patterns and platforms for innovation and optimisation.
• Ensure solutions meet enterprise architecture standards, security policies, regulatory requirements and best practices.
• Collaborate with stakeholders and product owners, and provide architectural oversight from design through to implementation.

Required profile

• Proven experience as a Solution Architect, Enterprise Architect or equivalent senior architecture role.
• TOGAF certification (mandatory).
• Demonstrable experience in at least one area: AI/ML solution architecture, generative AI, LLMs, intelligent automation, AI integration and governance, or data architecture, data engineering, data lakes/warehouses/lakehouse and data governance.
• Experience producing architecture diagrams, solution designs, technical documentation and roadmaps.
• Excellent stakeholder management and communication skills with business and technical audiences.
• Desirable: financial services, banking, insurance or large enterprise experience; cloud-native, microservices and API-led integration exposure; cybersecurity and data privacy knowledge; experience leading digital transformation programmes.

Required skills

• Strong understanding of enterprise architecture principles, frameworks and governance.
• Cloud architecture across AWS, Azure or GCP.
• Data architecture, data engineering, data integration and data management.