Senior Product Manager - Fraud Automation
Senior Product Manager at Wise owning the strategy and roadmap for AI-powered fraud investigation automation, combining GenAI, agentic workflows, and human oversight to automate FinCrime investigations end to end. Works hands-on with engineering, data science, design, and compliance to ship safe, scalable, compliant automation.
- Compensation
- Not disclosed
- Location
- London, gb
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Product
- Posted
Skills
Must have
- Experienced in Product Management with a track record of leading teams and shipping impactful solutions
- Hands-on: comfortable moving between product strategy and detailed product work
- Experience shipping GenAI products in production that automated work previously done by people
- Fluent in AI product development: prompt systems, LLM evaluation, agentic workflows, system architecture, failure modes, monitoring, feedback loops, safe rollout
- Data-driven: process mapping, quantitative and qualitative evidence, turning ambiguity into hypotheses and decisions
- Strong cross-functional leadership: aligning teams with different expertise, incentives, and constraints
- Always learning and iterating: eager to test, refine, and improve safety features from real-world data
Full description
We are looking for a Senior Product Manager to own the vision and roadmap for AI-powered fraud investigations and automation. Your scope will span automating investigation workflows, information collection, and decisioning, as well as building reusable automation capabilities that can scale across FinCrime.
You will work with Engineering, Data Science, Design, Operations, Risk, and Compliance to combine AI with human expertise and build automated fraud investigation processes that are accurate, scalable, and compliant. You will decide how deterministic logic, machine learning, GenAI, agentic workflows, operational change, and human judgement should work together to take our anti-fraud programme to the next level.
What You’ll Be Doing
- Own the Fraud Automation strategy and roadmap - Define how Wise will automate fraud investigations, identify and prioritise the highest-impact opportunities, and take end-to-end accountability from discovery through production rollout, measurable impact, and continuous improvement.
- Solve problems without a playbook - Explore new ways to automate complex fraud investigations, experiment with emerging technology, and turn unproven ideas into safe, scalable, production-ready solutions.
- Combine strategic ownership with hands-on execution - Set the product direction while rolling up your sleeves to work directly with investigators, fraud cases, data, processes, and technology. Wear different hats when needed to help the team learn faster and ship high-quality solutions today rather than tomorrow.
- Build safe and compliant automation - Establish rigorous evaluation, backtesting, QA, monitoring, governance, auditability, human oversight, and feedback loops so AI-powered fraud investigations can scale while maintaining a high bar for customer safety, decision quality, and regulatory compliance.
- Build scalable, reusable automation foundations - Partner across Wise to turn successful fraud use cases into shared capabilities that simplify end-to-end workflows and support broader Fraud and FinCrime needs.
- Drive measurable impact – Ensure that our investments in automation space lead to scalability of our prevention program, higher customer confidence, and friction that only exists where truly necessary.
✅ Experienced in Product Management – You’ve led product teams in and have a track record of shipping impactful solutions.
✅ Hands-on - You are comfortable moving between product strategy and the detailed work needed to improve the product.
✅ Experienced with GenAI products in production - You have shipped products that use GenAI to automate work previously performed by people.
✅ Fluent in AI product development - You understand prompt systems, LLM evaluation, agentic workflows, system architecture, failure modes, monitoring, feedback loops, safe rollout, and when AI is not the right solution.