Top Tech Jobs & Startup Jobs

Design, build, and scale production-grade, stateful autonomous AI agents; integrate agents into payments, fraud, and core product systems; implement LLMOps, observability, and evals-as-code; optimize RAG/vector DB pipelines for performance and cost; handle containerization, CI/CD, and post-launch stability; mentor engineers and drive best practices.

Lead loss mitigation, build predictive collections models and CECL loss forecasts, design automated conversational recovery strategies, manage credit loss budgeting and vendor selection, and present findings to executive leadership.

The Fraud Investigations Specialist is responsible for bridging the gap between operational investigators and technical teams, conducting data-driven investigations, and identifying fraud patterns through SQL queries. They monitor fraud metrics, provide insights, and collaborate on fraud rule creation.

Lead fraud detection and mitigation for a conversational Send Now Pay Later product: define first-party fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, integrate ML and decisioning tools (Taktile), and coordinate SARs and compliance reporting.

Design, build, and scale production-grade, stateful AI agent systems integrated into core product flows. Implement LLMOps, observability, containerized CI/CD deployments, RAG/vector DBs, evaluation pipelines, performance/cost optimizations, and mentor junior engineers.

The AI Engineer will design, build, and scale autonomous AI agents, optimizing LLM capabilities and integrating them into the product, ensuring functionality across financial services.

Lead fraud detection and mitigation for a conversational BNPL product: define fraud typologies, analyze repayment/chargeback trends, own fraud KPIs, design policies, collaborate on ML models and decisioning workflows, and coordinate SARs with Compliance.

Design and own loss mitigation and loss-forecasting frameworks (CECL), build predictive collections models and automated contact strategies (WhatsApp/SMS/omnichannel), align with Operations for recovery execution, manage credit loss budgeting and capacity planning, and lead vendor evaluation and onboarding to maximize recovery ROI.

Analyze fraud patterns and metrics to reduce fraud losses and false positives. Build dashboards, fraud features, rules, and models. Perform human-in-the-loop reviews, improve operational processes, and provide actionable insights to Risk Operations, Payments, Growth, and senior management.

Lead loss mitigation, forecasting, and collections strategy for consumer lending. Build predictive collections models and CECL-based loss forecasts, align conversational operations, manage credit loss budgeting and vendor procurement, and present results to executive stakeholders.