About the job

About the RoleWe are building the next generation of AI-native platforms for real estate — spanning intelligent marketplaces, agentic transaction workflows and data-driven investment tooling — with engineering in London and operating businesses in Saudi Arabia and the wider Gulf. The Head of AI Engineering & Architecture owns the end-to-end technical architecture of the platform and leads the engineering organization that builds it. The role converts product and commercial ambition into a scalable, secure and compliant technology estate, and sets the engineering standards, tooling and culture for a fast-scaling AI venture.

• Key ResponsibilitiesArchitecture — Define and own the target-state architecture across the platform: multi-tenant SaaS core, LLM and agentic orchestration layers, retrieval and vector infrastructure, data platform and APIs.
• Engineering leadership — Build, lead and scale the AI engineering function in London — hiring, organization design, performance management and succession — while coordinating with distributed development teams in the Gulf and India.
• AI/ML platform — Establish the model strategy: selection and evaluation of foundation models, fine-tuning and RAG patterns, agent frameworks, guardrails, evaluation harnesses and cost/latency optimization.
• MLOps & reliability — Stand up production-grade MLOps and LLMOps — CI/CD, observability, model monitoring, drift detection, prompt and version management — with clear SLOs for reliability and performance.
• Cloud & infrastructure — Own cloud architecture and infrastructure economics (AWS/Azure/GCP), including data residency design for Saudi-hosted workloads and multi-region deployment.
• Security & compliance — Embed security and privacy by design; ensure the platform meets UK GDPR and Saudi PDPL requirements and supports sector regulatory obligations (REGA/FAL, and SAMA where financial-services use cases apply), working with legal and compliance counterparts.
• AI governance — Institute AI governance: model risk management, human-in-the-loop controls, auditability, red-teaming and responsible-AI standards suitable for board and investor scrutiny.
• Stakeholder partnership — Partner with the Head of AI Product on roadmap feasibility, technical discovery and build/buy/partner decisions; present architecture and delivery status to the CTAIO, board and investors.
• Vendors & partnerships — Manage vendor and partner ecosystem — model providers, cloud, data and tooling — including commercial negotiation and technical due diligence.
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