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About the role
The Group IT Data Team is building scalable, governed, enterprise-grade AI capabilities to improve operational efficiency and unlock business value across FEO's business units. As AI Architect, you will be the enterprise design authority for AI architecture, defining reference architectures, platform standards, solution patterns, governance controls and technical roadmaps. This role suits a senior architect with deep hands-on experience in Generative AI, LLMs, RAG and AI-ready data platforms who can guide delivery teams from concept through to production.
What you'll do
Define enterprise AI reference architectures, platform standards, reusable solution patterns and technical roadmaps aligned to AI strategy, enterprise architecture, cybersecurity, data governance and business priorities.
Lead architecture design for GenAI, LLM, RAG, AI agents, multi-agent workflows, conversational AI, document intelligence, recommendation engines, predictive ML, computer vision and NLP solutions.
Evaluate and select AI/ML technologies, foundation models, LLM providers, open-source models, orchestration frameworks, vector databases, cloud AI services and AI infrastructure components based on use case, risk, cost, performance, data residency and integration needs.
Design AI-ready data foundations including document ingestion, chunking, embeddings, vector search, hybrid search, re-ranking, knowledge graphs, metadata schemas, data lineage, source attribution and access-aware retrieval.
Define and implement LLMOps/MLOps practices including model registry, prompt and pipeline versioning, evaluation frameworks, observability, monitoring of latency, quality and cost, model drift detection, retraining triggers and deployment controls across DEV/UAT/PROD environments.
Architect scalable AI platform environments across cloud, hybrid and on-premises architectures, including secure APIs, microservices, containers, CI/CD pipelines, AI gateways, observability and cost optimisation.
Ensure secure integration with enterprise systems including ERP, CRM, data platforms, document management systems, IAM/SSO, workflow systems and external APIs.
Establish Responsible AI and AI governance controls, including human-in-the-loop design, explainability, bias mitigation, prompt injection protection, content safety, PII and confidential data handling, auditability, model risk controls and compliance with internal policies and applicable Singapore regulatory expectations.
Partner with business units to shape AI use cases, assess value and feasibility, define architecture options, recommend buy/build/partner approaches and guide pilots through production scaling.
Provide technical leadership to AI engineers, data engineers, solution architects, vendors and delivery teams through architecture reviews, design documentation, technical standards, mentoring and best-practice sharing.
Maintain awareness of emerging AI technologies, agentic AI patterns, multimodal AI, model-con
Requirements
At least 8–12 years of experience in software engineering, data engineering, cloud architecture, enterprise architecture or AI/ML-related roles; 12+ years preferred for Principal/Expert level
At least 3–5 years of hands-on experience designing, architecting or delivering production AI/ML, GenAI, LLM or data/AI platform solutions
Strong hands-on knowledge of GenAI/LLM technologies such as Azure OpenAI, OpenAI-compatible APIs, AWS Bedrock, Google Vertex AI, SAP AI capabilities or equivalent enterprise AI platforms
Strong understanding of RAG architecture, including document ingestion, chunking, embeddings, vector databases, hybrid search, re-ranking, prompt design, source attribution and evaluation
Experience with AI orchestration and agent frameworks such as Semantic Kernel, LangChain, LlamaIndex, LangGraph, AutoGen, CrewAI or equivalent
Strong understanding of MLOps/LLMOps including CI/CD, model registry, deployment automation, monitoring, observability, drift detection, evaluation and model/prompt lifecycle management
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