AI Product & Business Process Manager

Role purpose Own the discovery, prioritisation and delivery of AI products and process improvements across the brokerage. Translate business challenges into well-defined solutions that improve operational efficiency, employee productivity and client service. Work with functional leaders and technical teams to move initiatives from business case through implementation, adoption and measurable benefit realisation. Key responsibilities Business discovery and prioritisation • Map workflows across client onboarding, KYC operations, payments, client support, sales, compliance, dealing support and management reporting; identify delays, manual handling, control weaknesses and avoidable rework. • Build and maintain a prioritised AI and automation backlog, assessing business value, client impact, process readiness, data availability, delivery effort and operational risk. • Develop business cases with baseline volumes, handling time, error rates, implementation costs and ongoing model or platform costs; agree how benefits will be measured with Finance and process owners. • Select the appropriate intervention for each problem, including process simplification, rules-based automation, predictive models, generative AI or a combination. Product definition and delivery • Write product requirements, user journeys, process maps, user stories and acceptance criteria covering normal operation, exceptions, approval steps, access rights and audit evidence. • Define brokerage use cases such as an internal policy assistant, support copilot, onboarding document triage, payment exception investigation and automated operational reporting. • Coordinate engineering, data, security, compliance and business stakeholders through design, development, user acceptance testing and controlled release; resolve dependencies and scope changes. • Specify human review, escalation and fallback requirements for sensitive outputs, including client communications, payment actions and any decision affecting trading accounts. Adoption and continuous improvement • Own launch readiness, updated procedures, training materials, stakeholder communication and post-launch support arrangements with the relevant operational teams. • Monitor adoption, process completion, exception volumes, client outcomes and cost per completed task; distinguish time saved from independently verified financial savings. • Collect user feedback and analyse workflow data to improve usability, remove bottlenecks and retire initiatives that do not demonstrate value. • Maintain product documentation, release decisions and benefits reporting; present progress, trade-offs and delivery risks to the Head of AI & Automation. Essential experience and qualifications • 6+ years in product management, business analysis, process improvement or digital transformation, including ownership of technology-enabled change from discovery to adoption. • At least 2 years delivering AI, intelligent automation or data products with measurable business outcomes; experience beyond demonstrations or vendor selection alone. • Experience in a CFD or FX brokerage, securities business, payments company or comparable financial services environment; understanding of the brokerage client lifecycle. • Ability to define requirements for LLM applications, workflow automation, APIs and data products without relying on engineers to establish the business problem. • Strong process mapping, prioritisation, requirements writing, UAT, change management and stakeholder management skills; comfortable challenging weak assumptions. • Ability to interpret operational data using SQL, BI tools or advanced spreadsheets and to communicate recommendations clearly to technical and senior business audiences. • Bachelor’s degree in Business, Engineering, Computer Science or a related discipline, or equivalent relevant professional experience. Preferred experience • Direct experience with CRM, trading back-office systems, client portals, KYC platforms or support platforms in an FX/CFD business. • Experience with BPMN, Lean or Six Sigma methods, experimentation and benefits validation with Finance. • Experience introducing AI products across several departments, entities or languages. Show more Show less

6+ years in product management, business analysis, process improvement or digital transformation, including ownership of technology-enabled change from discovery to adoption. At least 2 years delivering AI, intelligent automation or data products with measurable business outcomes; experience beyond demonstrations or vendor selection alone. Experience in a CFD or FX brokerage, securities business, payments company or comparable financial services environment; understanding of the brokerage client lifecycle. Ability to define requirements for LLM applications, workflow automation, APIs and data products without relying on engineers to establish the business problem. Strong process mapping, prioritisation, requirements writing, UAT, change management and stakeholder management skills; comfortable challenging weak assumptions. Ability to interpret operational data using SQL, BI tools or advanced spreadsheets and to communicate recommendations clearly to technical and senior business audiences. Bachelor’s degree in Business, Engineering, Computer Science or a related discipline, or equivalent relevant professional experience.

Role purpose: Own the discovery, prioritisation and delivery of AI products and process improvements across the brokerage. Translate business challenges into well-defined solutions that improve operational efficiency, employee productivity and client service. Work with functional leaders and technical teams to move initiatives from business case through implementation, adoption and measurable benefit realisation. Key responsibilities include: Business discovery and prioritisation (map workflows across client onboarding, KYC operations, payments, client support, sales, compliance, dealing support and management reporting; build and maintain a prioritised AI and automation backlog; develop business cases with baseline metrics; select appropriate intervention). Product definition and delivery (write product requirements, user journeys, process maps, user stories, acceptance criteria; define brokerage use cases; coordinate engineering, data, security, compliance and stakeholders; specify human review and fallback requirements). Adoption and continuous improvement (launch readiness, training, post-launch support; monitor adoption and savings; collect user feedback and retire non-value initiatives; maintain documentation and benefits reporting; present progress and risks to Head of AI & Automation).