Senior Product Manager – Fraud Automation

Overview

As Senior Product Manager, you will own the vision and roadmap for AI-powered fraud investigations and automation at Wise. You’ll collaborate with Engineering, Data Science, Design, Operations, Risk, and Compliance to blend AI with human expertise and deliver scalable, compliant investigation workflows. You will balance deterministic logic, GenAI, and human judgment to advance Wise’s anti-fraud program. This role offers the chance to shape reusable automation foundations that scale across FinCrime and improve customer safety and trust.

Pay / Benefits

• Meaningful global impact
• Autonomy and roadmap ownership
• Work at the edge of AI and FinCrime
• Growth and career development opportunities
• Global offices in London, Tallinn, Budapest

Responsibilities

• Define and own the fraud automation strategy and end-to-end roadmap from discovery to production rollout
• Explore and prototype novel automation approaches for complex fraud investigations
• Lead cross-functional collaboration to ship high-quality AI-powered solutions
• Establish governance, evaluation, backtesting, monitoring, and safety controls for scalable automation
• Build reusable automation foundations and partner across Wise to broaden fraud/FinCrime capabilities
• Drive measurable impact by scaling prevention programs and increasing customer confidence

Key requirements

• Experienced product manager with a track record of shipping impactful solutions
• Hands-on with both strategy and execution
• Experience shipping GenAI-powered products in production
• Fluent in AI product development including prompt systems, LLM evaluation, agentic workflows, system architecture, monitoring, and safe rollout
• Data-driven with strong hypothesis-driven decision making
• Strong cross-functional leadership and ability to align diverse teams
• Curious and iterative mindset with focus on safety improvements based on data and user behavior

• Cross-functional collaboration
• Data-driven decision making
• Adaptability and hands-on execution
• GenAI in production
• Prompt engineering
• LLM evaluation

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