AI Architect – Enterprise AI Design Lead

About the role

The Group IT Data Team is building enterprise‑grade AI capabilities to drive operational efficiency and digital transformation across the real‑estate value chain. As the AI Architect you will act as the enterprise design authority, shaping AI reference architecture, platform standards and technical roadmaps while translating business outcomes into production‑ready AI solutions.

Key responsibilities

• Define and maintain enterprise AI reference architectures, platform standards and reusable solution patterns aligned with the organization’s AI strategy and governance.
• Lead design of Generative AI, Large Language Model (LLM), Retrieval‑Augmented Generation (RAG), AI agents, 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 and cloud AI services based on risk, cost, performance and data residency.
• Design AI‑ready data foundations including document ingestion, chunking, embeddings, vector and hybrid search, knowledge graphs, metadata schemas, data lineage and access‑aware retrieval.
• Implement MLOps/LLMOps practices: model registry, versioning, evaluation, observability, monitoring, drift detection and automated retraining pipelines.
• Architect scalable AI platform environments across cloud, hybrid and on‑premises infrastructures, ensuring secure APIs, microservices, containers, CI/CD pipelines and cost optimisation.
• Integrate AI solutions securely with enterprise systems such as ERP, CRM, data platforms, document management, IAM/SSO and external APIs.
• Establish Responsible AI and governance controls, including human‑in‑the‑loop, explainability and bias mitigation.

Required profile

• Proven experience designing and delivering enterprise AI solutions at scale.
• Strong understanding of AI governance, security and data‑privacy requirements.
• Ability to work closely with business leaders, technology teams, vendors and partners.
• Excellent communication skills to translate complex technical concepts into business value.

Required skills

• Generative AI and Large Language Models (LLMs)
• Retrieval‑Augmented Generation (RAG) and AI agents
• MLOps / LLMOps practices
• AI‑ready data platforms and vector databases
• Hybrid search, embeddings and knowledge graph design
• CI/CD pipelines, microservices and containerisation
• API design and secure integration with ERP, CRM and IAM/SSO systems
• Cloud AI services (AWS, Azure, GCP) and AI governance frameworks