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 ResponsibilitiesDesign 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 systemsReview and approve all architectural deliverables from external AI vendors and technology partnersLead hyperscaler engagement (Microsoft Azure, Google Cloud, AWS) and coordinate with solution architects to ensure best-practice, cost-optimised implementationDefine and enforce AI engineering standards: API design, model evaluation frameworks, security and privacy controls, and MLOps governanceProvide architectural guidance on phased migration from legacy Java estate to AI-native componentsEvaluate and select AI technologies including LLM frameworks, vector databases, embedding models, and orchestration platformsLead technology risk assessment and mitigation, including model bias evaluation, data security architecture, and vendor lock-in risk managementMentor and develop internal technical staff as part of the organisation's reskilling programmeContribute to long-term AI product roadmap and emerging technology assessmentRequired Skills & Abilities10+ years in enterprise solution or technical architecture3+ years designing and deploying production LLM/AI systems at enterprise scaleDeep expertise in LLM architecture patterns: RAG, fine-tuning, prompt engineering, and agentic frameworksHands-on experience with at least two of: Azure OpenAI, Google Vertex AI, AWS BedrockStrong enterprise integration background — API design, event-driven architecture, and data pipelinesExperience governing multi-vendor technology delivery programmesSecurity-first mindset with working knowledge of AI risk frameworks (NIST AI RMF, MAS AI governance)Good command of written and spoken EnglishLogistics, supply chain, or manufacturing domain experienceExperience with Java system integration and legacy modernisationPublished architectural decision records or open-source AI contributionsFamiliarity with Singapore's IMDA AI governance guidelines