About Moneybox At Moneybox, our mission is to give everyone the means to get more out of life. We're guided by our belief that wealth isn't about the money, it's about the means to more - more freedom, opportunities, possibilities, and peace of mind. Moneybox is an award-winning wealth management platform, helping over one and a half million people build wealth throughout their lives, whether they’re saving and investing, buying their first home, or planning for retirement.
Job Brief Moneybox engineering serves more than 2M customers and runs a live service handling over 20M API requests a day. We have agreed a company-wide AI Platforms strategy, backed by a business case, and we are now building the team to deliver it. This is a newly created function and you will be its first hire. The Head of AI Platforms & Deployment is a player-manager role reporting to the Engineering Director, owning both sides of that strategy: the AI Platforms capability pillars (control, monitoring and sandboxing; agentic workflow orchestration; knowledge capture) and the AI Deployment team of forward-deployed engineers who put AI to work on real business problems.
You will be hands-on from day one - enabling business deployment of AI with the tools we have today - whilst also building and delivering a business-driven, multi-year AI platforms strategy and hiring and managing the team that executes it. Why now: AI offers Moneybox significant opportunities, and unlocking them safely means managing the risks that come with it. The controls and capabilities that make that possible (gateways, sandboxing, guardrails, monitoring, perimeter defence) need dedicated leadership to build.
Demand for AI-enabled business systems is real and, without a safe path, goes underground. Someone must own the graduation ladder from "works for me" to owned, reviewed business system. We are hosting customer-facing AI models as part of our Aurora financial guidance service. Serving these safely, securely and at scale needs a dedicated engineering owner. We need to evolve our current Claude, Gemini and other frontier LLM deployments into a coherent, safe and effective strategic deployment platform.
You are not coming in to write a strategy deck. Pace and learning are key: we expect you to run two tracks in parallel from day one - enable the do-ers , helping the business use AI safely with what we have today rather than gating everything behind platform build, and build the strategic platform . Key decisions should be made within your first two to three months and material platform improvements live within six.
You will hire further engineers before the end of the year, growing the team as the benefits compound. What You'll Do Own the AI platform strategy. Risk management, horizon scanning, supplier selection and vendor management, business case ownership, and benefits realisation through a coherent, business-driven delivery roadmap that is trusted by stakeholders across Moneybox. Build and lead the AI Deployment team.
Hire, line-manage and set the engagement priorities and delivery standards for a team of forward-deployed AI engineers, working alongside embedded specialists while we hire. Grow into managing both the platform and deployment sub-teams as the function expands. Own perimeter safety in an AI-native world. Set and own our defensive AI strategy, with execution carried out in collaboration with Tech Ops.
Our Principal Cloud Architect, who owns overall cloud strategy, is a key partner. Own AI platforms and costs. Harnesses, tooling, cost management, forecasting and optimisation (including usage-based pricing shifts), and the staff access model. This includes: AI safety for internal use : sandboxing, policy, integrations, MCP governance, usage guardrails and monitoring expectations. The three platform pillars : control, monitoring and sandboxing (LLM and MCP gateway, anonymisation, local hardening, sandboxed cloud agent hosting); agentic workflo