We are a leading logistics and supply chain group undergoing a major AI transformation programme. We are seeking an experienced AI Architect to serve as the technical conscience of our AI initiative — owning architectural integrity, governing vendor deliverables, and ensuring our LLM Intelligence Engine is built on sound, scalable, and cost-efficient foundations.
This is a strategic, hands-on leadership role that sits at the intersection of vision and execution.
Primary Responsibilities
- Design and own the end-to-end architecture of our LLM Intelligence Engine, including model selection, RAG pipeline design, agent frameworks, and integration with legacy Java systems
- Review and approve all architectural deliverables from external AI vendors and technology partners
- Lead hyperscaler engagement (Microsoft Azure, Google Cloud, AWS) and coordinate with solution architects to ensure best-practice, cost-optimised implementation
- Define and enforce AI engineering standards: API design, model evaluation frameworks, security and privacy controls, and MLOps governance
- Provide architectural guidance on phased migration from legacy Java estate to AI-native components
- Evaluate and select AI technologies including LLM frameworks, vector databases, embedding models, and orchestration platforms
- Lead technology risk assessment and mitigation, including model bias evaluation, data security architecture, and vendor lock-in risk management
- Mentor and develop internal technical staff as part of the organisation's reskilling programme
- Contribute to long-term AI product roadmap and emerging technology assessment
Required Skills & Abilities
- 10+ years in enterprise solution or technical architecture
- 3+ years designing and deploying production LLM/AI systems at enterprise scale
- Deep expertise in LLM architecture patterns: RAG, fine-tuning, prompt engineering, and agentic frameworks
- Hands-on experience with at least two of: Azure OpenAI, Google Vertex AI, AWS Bedrock
- Strong enterprise integration background — API design, event-driven architecture, and data pipelines
- Experience governing multi-vendor technology delivery programmes
- Security-first mindset with working knowledge of AI risk frameworks (NIST AI RMF, MAS AI governance)
- Good command of written and spoken English
- Logistics, supply chain, or manufacturing domain experience
- Experience with Java system integration and legacy modernisation
- Published architectural decision records or open-source AI contributions
- Familiarity with Singapore's IMDA AI governance guidelines
