Head of AI Platforms & Deployment

Overview

In this role you will own Moneybox’s AI platforms strategy and lead the AI Deployment team, delivering a business-driven, multi-year roadmap while enabling safe AI use today. You’ll manage risk, vendors, and costs, and partner with Tech Ops, Decisioning, and Data Science to scale customer-facing AI models on Aurora. This is a hands-on leadership role that starts with building the team and establishing governance, guardrails, and platform foundations. You’ll drive cross-functional impact across the organization and shape the long-term AI-enabled transformation.

Responsibilities

• Define and own the AI platform strategy and execution roadmap
• Build and lead the AI Deployment team of forward-deployed engineers
• Own perimeter safety and defensive AI strategy in collaboration with Tech Ops
• Manage AI platform costs, tooling, forecasting, and usage-based pricing
• Oversee model hosting, scaling, safety, and performance for customer-facing AI
• Enable departments with practical, risk-assessed AI usage today and streamline demand through front-door channels
• Evolve and integrate platform pillars: control, monitoring, sandboxing, agentic workflows, knowledge capture
• Align deployments with strategic direction and continuously improve existing AI deployments
• Partner with Cloud Architecture, Decisioning and Data Science on governance and risk
• Drive vendor management, supplier relationships, and business-case justification
• Hire, develop, and scale the AI platforms and deployment team as the function grows
• Balance hands-on involvement with strategic leadership in early months of the role

Key requirements

• Proven engineering leadership with experience managing engineers and budgets
• Led an AI platform or enablement capability in the last 2–3 years
• Built or significantly scaled a team
• Fluency with frontier AI stacks, agentic tooling, MCP, evaluations, prompts engineering
• AI security and governance experience: sandboxing, gateways, guardrails, data-boundary reasoning
• Cost engineering: usage-based pricing, forecasting and optimisation
• Software and cloud architecture depth to collaborate with Architects and Tech Ops
• Vendor evaluation and management in a fast-moving market
• Ability to articulate platform investment in ROI/EBITDA to non-technical executives

• cross-functional collaboration
• strong stakeholder management
• commercial literacy
• frontier model platforms
• agentic tooling and harnesses
• MCP gateways and integrations

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