Head of Data / AI (J-2629)

AI / Data Platform Architecture & Development

• Lead the design, development, and scaling of robust AI/ML platforms and infrastructure (on-premises and hybrid).
• Drive MLOps, LLMOps, and AgentOps practices to accelerate model development, deployment, and lifecycle management.
• Deploy, optimize, and scale Large Language Model (LLM) and agent workflows with a focus on performance, cost, reliability, and observability.
• Develop, optimise, and maintain robust ETL/ELT pipelines for data ingestion, transformation, and loading from internal systems, external feeds, and market data sources.
• Architect and implement a modern data warehouse / Lakehouse, including data modelling standards, dimensional modelling, and performance optimisation.
• Collaborate with AI and business teams to deliver clean, feature-ready data for models, RAG systems, and decision-making use cases.
• Fine-tune models, design robust evaluation and monitoring systems, and implement multi-agent architectures with appropriate guardrails.
• Evaluate emerging technologies, lead proof-of-concept initiatives, and implement Infrastructure-as-Code (Kubernetes, etc.).

Team Leadership & Business Alignment

• Build, mentor, and lead a high-performing AI solution team.
• Champion the adoption of AI-assisted development practices across the organisation.
• Serve as the key bridge between business stakeholders and technical teams, translating requirements into deliverable AI initiatives.
• Actively contribute hands-on through architecture reviews, solution design, and critical implementation work.

Infrastructure, Operations & Governance

• Ensure high availability, performance, and cost-efficiency of AI infrastructure.
• Maintain secure, compliant, and repeatable deployment processes in line with regulatory standards.
• Manage operational excellence, incident response, and continuous improvement of AI platforms.