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.

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.

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.

Lead and mentor an AI engineering squad to design scalable architectures, prioritize technical roadmap with Product, track metrics (usability, retention, F1), drive deliverables, optimize processes, leverage AI tooling, and produce documentation to enable long-term technical success.

Lead credit analytics for the Send Now Pay Later product: build and optimize valuation, vintage and NPV models; manage credit policies, portfolio monitoring, and NPL reporting; integrate and test scoring models with engineering/data science; and research alternative data to improve predictive performance.