Key Responsibilities

• Own the product vision, roadmap, and execution for AI-powered tools within MarTech, starting with creative operations such as asset (static and video) generation, tagging, versioning, and QA
• Build and scale autonomous or semi-autonomous agents to support localisation, campaign setup, QA, trend analysis, reporting, and more
• Act as the team’s thought leader in AI design patterns, specifically for marketing and product operations

Cross-Functional Collaboration

• Partner with developers, data engineers, and creative stakeholders to embed AI into everyday workflows
• Collaborate with paid marketing, CRM, and Organic squads to identify automation opportunities and redesign existing processes

Experimentation and Deployment

• Define experiments and MVPs to test and validate AI applications before scaling
• Lead prompt engineering, tool selection, fine-tuning, and guide engineering handover for productionisation
• Drive adoption through internal demos, workshops, and clear documentation

Governance and Ethics

• Ensure all AI solutions comply with internal governance and ethical standards, including explainability, auditability, and human-in-the-loop where necessary

Required Skills

• Hands-on AI practitioner: You have built or product managed agentic solutions using frameworks like LangChain, OpenAI Functions, Claude, or ReAct
• Proven Product Owner: You know how to write user stories, prioritise backlogs, and deliver tools in an agile, iterative environment
• Marketing-aware: You understand the fundamentals of creative production, CRM, or paid media operations, and appreciate the nuance in each workflow
• Design-focused: You can map and analyse processes to identify meaningful areas where AI can be applied to improve outcomes
• Clear communicator: You are able to explain technical concepts to a non-technical audience and influence cross-functional stakeholders

Nice to Have

• Experience in growth, ad operations, or lifecycle marketing
• Familiarity with CMS, DAM, CDP, CRM and equivalent MarTech infrastructure
• Knowledge of vector databases, embeddings, or retrieval-augmented generation (RAG)

Candidate Journey

• Recruiter call
• Meet a team member
• Skills assessment
• Meet the Leadership team