AI Architect (Group IT)

About the role

The Group IT Data Team is building scalable, governed, enterprise-grade AI capabilities to improve operational efficiency and support digital transformation across FEO's business units. The AI Architect is the enterprise design authority for AI architecture, defining reference architectures, platform standards, solution patterns, governance controls and technical roadmaps. The role focuses on Generative AI, large language models, AI agents, RAG, AI-ready data platforms and MLOps/LLMOps, and guides delivery teams from concept through production.

Key responsibilities

• Define enterprise AI reference architectures, platform standards, solution patterns and roadmaps aligned with FEO's AI strategy, enterprise architecture, cybersecurity and data governance.
• Lead architecture design for GenAI, LLMs, RAG, AI agents, multi-agent workflows, conversational AI, document intelligence, recommendation engines, predictive ML, computer vision and NLP.
• Evaluate and select AI/ML technologies, foundation models, LLM providers, orchestration frameworks, vector databases and cloud AI services based on use case, risk, cost, performance, data residency and integration needs.
• Design AI-ready data foundations for RAG and agentic AI, including document ingestion, chunking, embeddings, vector search, hybrid search, re-ranking, knowledge graphs, metadata schemas, data lineage and access-aware retrieval.
• Define and implement LLMOps / MLOps practices: model registry, prompt and pipeline versioning, evaluation, observability, latency/quality/cost monitoring, drift detection, retraining triggers and deployment controls across DEV/UAT/PROD.
• Architect scalable AI platform environments across cloud, hybrid and on-premises setups, including secure APIs, microservices, containers, CI/CD pipelines, AI gateways and cost optimisation.
• Ensure secure integration with ERP, CRM, data platforms, document management systems, IAM/SSO, workflow systems and external APIs.
• Establish Responsible AI and governance controls: human-in-the-loop design, explainability, bias mitigation, prompt injection protection, content safety, PII handling, auditability and model risk controls, including Singapore regulatory expectations.
• Partner with business units on use cases, feasibility, architecture options and buy/build/partner choices, and guide pilots to production scale.
• Provide technical leadership to engineers, data engineers, solution architects and vendors through reviews, documentation, standards and mentoring.

Required profile

• At least 8-12 years of experience in software engineering, data engineering, cloud architecture, enterprise architecture or AI/ML 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.
• Degree in Computer Science, Information Technology, Engineering, Data Science, AI or equivalent; Master's degree or relevant architecture/cloud/AI certifications preferred.
• Strong communication, stakeholder management, documentation and technical leadership skills, with the ability to mentor engineers.

Required skills

• Hands-on knowledge of GenAI/LLM platforms such as Azure OpenAI, OpenAI-compatible APIs, AWS Bedrock, Google Vertex AI or SAP AI capabilities.
• RAG architecture and AI orchestration frameworks such as Semantic Kernel, LangChain, LlamaIndex, LangGraph, AutoGen or CrewAI.
• MLOps / LLMOps, including CI/CD, model registry, deployment automation, observability and drift detection.
• Cloud architecture, preferably Azure, with working knowledge of AWS or GCP.
• Python and SQL, APIs, microservices, data pipelines and containers (Docker, Kubernetes, GitHub Actions, Azure DevOps).
• Enterprise data architecture (data lakes, warehouses, ETL/ELT, metadata, data quality, lineage, access control, governance) and AI security and governance.
• Experience with SAP ecosystem, Microsoft stack or real estate/hospitality/retail systems is an advantage.