…for Airwallex's Spend domain in the US, owning the technical strategy and architectural roadmap for products spanning corporate cards, expense management, and spend…

…services trends, regulatory requirements, risk management, fraud detection, customer analytics, and AI-driven innovation. Collaborate closely with Product Management, Engineering, Customer Success, and Consulting…

…Our daily customer engagements include conversations around how IoT can positively impact logistics management, workplace safety programs, fleet maintenance strategies, global asset management, and…

…You're humble and collaborative; turn zero‑to‑one ideas into real products, and you “get stuff done” end-to-end. You use AI…

…Product Manager to define, refine, and prioritise the quarterly roadmap, ensuring the team's work drives measurable impact on self-serve ARR and fraud…

…ABOUT THE TEAM The risk platform team at Airwallex is responsible for managing risk across all Airwallex products, including topics like GTPN, Payments, Issuing…

…What You Bring - 7+ years of product management, with significant ownership of complex, high-stakes, or AI products. This is a senior IC role…

…GenAI, LLMs, and AI-agent architectures to advance our abuse prevention capabilities. Key job responsibilities - Design, develop, and deploy production ML systems for abuse…

…WHAT YOU BRING - 7 to 10 years in product management or product strategy with leadership in identity, risk, fraud, HR or recruitment tech, or…

…high-performing GTM AI enablement team: recruit, mentor, and grow a team of enablement specialists, content creators, and program managers Set clear priorities and…

…fraud patterns evolve. - Identify and implement foundational improvements to how the team builds models. - You will collaborate across Engineering, Fraud Analytics, Product, and ML…

…Monitoring our Fraud and FinCrime metrics and drive action delivery with our product teams to address the trends. Combining hands-on execution with strategic…

…Product/Engineering to design risk tooling or automation, including use of AI/ML/LLMs in operations - Mandarin language proficiency. APPLICANT SAFETY POLICY: FRAUD AND…

…Work cross-functionally with Core Infrastructure, Product Management, and Data Science teams to translate business-level fraud patterns into robust algorithmic solutions. WHAT WE…

…faster, leveraging ML to confirm payments sooner, and unlocking payment capabilities that give merchants the best experience. The Senior Product Manager will work closely…

…Experience evaluating and testing ML and generative AI systems, including custom evals, benchmarking, stress testing, and drift/degradation monitoring. - Risk management experience: Demonstrated experience…

…assessments for new and existing products, features and AI/ML use cases (including automated decision‑making, profiling, biometrics, fraud/credit models), aligning recommendations with…

…secure SDLC, or AI/ML security risks - You've worked somewhere where PII or sensitive data was the core product The team Small and…

…Scale AI, Labelbox, Prodigy, or similar acceptable) Track record managing outsourced labeling vendors or BPOs for ML data production Familiarity with common ML labeling…

…experience, in addition to program management experience. Strong conceptual fluency in LLM-based products, AI infrastructure, and developer AI tooling - enough to ask the…

…the entire data and AI/ML lifecycle, simplifying the interface while providing proper safety and governance. This includes managing our data infrastructure (Databricks, Spark…

As Senior Data Scientist (Fraud/Financial Crime Analytics) you'll develop, train, deploy, and monitor predictive fraud and risk models and AI/ML Tools…

…PREFERRED QUALIFICATIONS - Experience designing and scaling incentive, rewards, or referral systems that drive measurable user and business outcomes. - Experience integrating ML models into production…

…3-8+ years in software product development, ideally in highly technical areas which may include AI/ML products, developer solutions, etc. A deep understanding…

…scientists, risk strategy specialists, analytics engineers, product managers, and operations teams. You will work across the full ML lifecycle—from problem formulation, feature engineering…