Description review
Head of Academy
CXM · Cyprus · back to the listing
HR standards
53/100
needs work
Title ↔ description
41/100
poor
Reads as
Product Manager
98% confident
What this role officially is
ICT product manager — ESCO, the EU occupation classification
ICT product managers analyse and define current and target status for ICT products, services or solutions. They estimate the cost effectiveness, points of risk, opportunities, strengths and weaknesses of products or services provided. ICT product managers create structured plans and establish time scales and milestones, ensuring optimisation of activities and resources.
Also known as: IT product manager, IT products manager, ICT product managers, ICT products manager, ICT products managers
How others title the same work
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What the listing never says
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
Head of Academy
Reporting LineReports 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.
LocationRemote (European timezone preferred). Occasional travel to group sales offices to engage with introducing brokers and understand client needs firsthand.
General PurposeThe 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.
Specific ObjectivesLaunch 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.
Key ActivitiesNothing 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.
Key CompetencesAI 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.
Likely Current JobAI 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.
Employer Value PropositionYou 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.
CompensationBase 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.
Assessment ProcessCandidates 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.
Originally posted on Himalayas
Reporting LineReports 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.
LocationRemote (European timezone preferred). Occasional travel to group sales offices to engage with introducing brokers and understand client needs firsthand.
General PurposeThe 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.
Specific ObjectivesLaunch 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.
Key ActivitiesNothing 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.
Key CompetencesAI 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.
Likely Current JobAI 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.
Employer Value PropositionYou 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.
CompensationBase 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.
Assessment ProcessCandidates 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.
Originally posted on Himalayas