Lead AI-driven AML capabilities at Wise, shaping the intelligence system powering risk mitigation. You will architect robust AI solutions, automate operational workflows, and build evaluation pipelines to reduce financial crime while supporting scale. You’ll guide technical strategy, mentor peers, and deploy production-grade models that augment human decision-making. This role offers impact across global operations and a chance to push frontier GenAI/LLM in financial crime prevention.
Pay / Benefits
Stock options in a profitable company
Hybrid working model
Annual personal development budget
Visa and relocation support
Responsibilities
Develop and deploy AI models to automate case summaries, red flag generation, risk classifications, and document requests within EDD workflows
Create labeling taxonomies with SMEs, build evaluation datasets, and implement automated evaluation harnesses
Lead prompt optimization experiments (few-shot, chain-of-thought, context ordering) to reduce hallucinations and drift
Design shadow testing and monitoring to safely evaluate prompts at scale and track data/output drift
Own production pipelines with production-ready Python services and maintain code quality under pressure to ship value
Implement human-in-the-loop architectures ensuring final decisions remain with human operators
Analyze upstream data to design strategies that deflect financial crime before reaching operations
Provide technical leadership and mentorship, shaping AI governance and architectural decisions
Key requirements
Experience building, training, testing, and evaluating ML systems
Strong Python knowledge; familiarity with OOP is a plus
Knowledge of GenAI/LLM solutions, evaluation harnesses, and prompt engineering
Experience with statistical analysis, experiment design, and failure mode analysis in LLM systems
Product mindset and ability to work across cross-functional teams
Good communication skills to convey technical concepts to SMEs
Strong problem-solving skills to refine problems and devise solutions
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