Head of Academy

Reports to the Chief Human Resources Officer (CHRO) for day-to-day operations, with a dotted line to the CEO for commercial outcomes. The CHRO at this organisation is a commercial role with direct accountability for business outcomes — not a back-office function.

No direct reports at this stage — the role operates as a solo lead, leveraging AI tooling in place of traditional headcount.

Remote (European timezone preferred). Occasional travel to group sales offices to engage with introducing brokers and understand client needs firsthand.

The Head of Academy builds and runs the group's AI-first online learning platform, serving two audiences with equal weight: helping traders develop the skills that keep them engaged and active, and equipping introducing brokers with the knowledge and tools to grow their client base and generate more business.

Launch the AI-personalised learning engine

Ship a working version of the personalised curriculum system — integrating with a trading analytics engine (Tradefora or equivalent) — so that course selection is driven by trader profile, stated goals, and actual trading behaviour, not manual browsing. Live within the first 90 days.

Drive measurable trader retention

Achieve a 10% improvement in trader retention attributable to Academy engagement, measured at 12 months against a pre-launch baseline. Trader engagement metrics — course completions, return logins, active learning sessions — serve as the leading indicators.

Build and measure IB development

Deliver a dedicated IB learning and content track — including edutainment and branded content designed to acquire as well as educate — with success measured by CRM-attributed trader acquisition. The target: participating IBs show a 10% uplift in new trader acquisition attributable to Academy-produced content within 12 months. Content consumption and distribution serve as supporting diagnostics.

Map the full trader journey

Document and partially build the end-to-end "Zero to Hero" pathway — from onboarding a new trader through to live trading, strategy codification, and agentic trading compatibility with MT5 and TradingView.

Convert IBs from non-exclusive to exclusive

Achieve a 20% increase in exclusive partnership agreements among Academy-engaged IBs within 12 months, driven by the tangible value the Academy delivers to their business.

Nothing exists yet — no platform, no content, no stack, no team. What follows is what building it from zero actually looks like.

Design and run AI-powered content workflows

Commission, quality-check, and iterate trading and IB education content using AI tooling — treating large language models and specialist AI agents as the primary content engine, with the role focused on prompt engineering, curation, and continuous improvement. This includes edutainment and branded content designed to acquire as well as educate.

Build and manage the personalisation layer

Connect trading data sources (including Tradefora or equivalent analytics integrations) to the learning platform via API, and configure AI-driven logic that matches each trader's profile, goals, and behavioural data to the right curriculum path.

Select and orchestrate the technology stack

Evaluate, choose, and integrate the platform, AI agents, and automation tools needed to run the Academy — remaining platform-agnostic and replacing traditional headcount with agent-based workflows wherever possible.

Own the IB learning track

Design and maintain a dedicated curriculum for introducing brokers, drawing on direct engagement with sales offices to understand what IBs actually need to grow their client base and onboard active traders.

Monitor performance and iterate

Track retention, engagement, and learning outcomes across both trader and IB audiences; use data to identify gaps, retire underperforming content, and prioritise the next build cycle.

AI tooling fluency

Proven ability to build workflows using LLMs, AI agents, and automation tools — not just as a user but as an orchestrator who can replace traditional headcount with agent-based processes.

AI-driven content creation

Able to use AI to research, write, structure, and iterate educational content at scale — comfortable with prompt engineering, output curation, and quality control without relying on human subject matter experts.

API integration and data literacy

Comfortable connecting platforms and data sources via API, and using trading or behavioural data to drive personalisation logic — no deep engineering required, but enough to own the integration decisions.

Solo operator mindset

Able to build, run, and iterate a multi-audience product without a team — self-directing, bias to action, comfortable with ambiguity in an early-stage environment.

Trading and financial markets knowledge

Sufficient understanding of retail trading, broker ecosystems, and the IB model to commission credible content and engage meaningfully with traders and IBs. An AI-native candidate is expected to close any gaps here quickly on the job.

Learning design awareness

A working grasp of curriculum structure and learner journeys — not a prerequisite, but something an AI-native candidate is expected to develop quickly on the job.

AI Automation Specialist / AI Workflow Builder

Someone currently building agent-based workflows and LLM-powered products — the closest direct match to how this role actually operates day-to-day.

Solo EdTech Builder / Online Course Creator

An independent operator who has built and monetised an online learning product, ideally using AI tooling to create and deliver content at scale.

Growth Hacker / No-Code Product Builder

Someone who has launched and iterated a digital product solo — comfortable with APIs, automation platforms, and a bias-to-action approach in an early-stage environment.

Digital Marketing Automation Lead

A marketer who has moved into AI-driven workflows — content at scale, personalisation logic, behavioural data — and is ready to own a product rather than a campaign.

Fintech or Trading Platform Product Manager

Someone with enough financial markets exposure to engage credibly with traders and IBs, who has pivoted toward AI-native ways of working.

You inherit an existing base of active traders and introducing brokers on day one — then build the Academy that monetises it. No cold-start problem, no fundraising, no co-founder risk: the distribution is already there, and your job is to build the engine that turns it into a business.

The hard part is real and worth naming: there is no platform, no content, no stack, and no team. You are building a product, a tech stack, a content engine, and a business model simultaneously — from a blank page. That's either the most exciting brief you've ever seen or the wrong role entirely. The right candidate will know which.

What makes it worth it: you are the Academy — sole decision-maker on strategy, stack, content, and growth — backed by the infrastructure, client base, and active support of a large multinational broker that has committed to making this work. The organisation is behind you. The starting conditions are genuinely favourable.

The financial upside is real and direct: profit share tied to the incremental business the Academy generates. The better you build it, the more you earn from it.

The starting model is lean and AI-first — you operate solo, with AI agents doing the heavy lifting. If the business grows to warrant it, so does the team. You shape what that looks like.

This role is for someone who has already built something meaningful with AI — and is done doing it for someone else's upside.

Base salary plus performance bonus. The bonus is tied to two primary revenue streams: incremental trader retention and IB business development. Educational services sales forms a third stream but is not a focus metric at this stage.

Candidates meet first with the CHRO, then with the CEO. Shortlisted candidates are asked to prepare a brief business plan and live demo — showing how they would approach building the Academy, including the AI tooling and workflows they'd put to work.