• Turn model capabilities into real product behavior. • Own problems end-to-end, from shaping model behavior, to building the systems around it, to ensuring it performs reliably in production. • Debug issues across the full stack (model, orchestration, infra, UX) • Optimize for latency, cost, and production reliability • Work closely with product and engineering to translate ambiguous problems into working systems

• Build and ship AI features end-to-end (model → system → user experience) • Design and iterate on prompts, tools, memory, and agent workflows • Turn raw model outputs into structured, reliable, and predictable behaviors • Debug issues across the full stack (model, orchestration, infra, UX) • Optimize for latency, cost, and production reliability • Develop lightweight evaluation frameworks to measure real-world performance • Work closely with product and engineering to translate ambiguous problems into working systems

• Build scalable, production-grade AI systems that automate and enhance credit analytics and credit decisioning workflows • Develop and integrate AI solutions across the credit lifecycle, including origination, underwriting, limit setting, portfolio monitoring, and model validation • Develop evaluation and guardrail frameworks to ensure response accuracy, reduce hallucinations, and support human-in-the-loop review, including offline testing with ground-truth datasets • Develop and operate enterprise-grade AI services with a focus on scalability, security, reliability, performance, and latency optimization • Implement LLMOps and GenAI operational practices, including prompt management, model versioning, monitoring, CI/CD pipelines, and observability for cost, latency, and response quality • Partner with analytics, engineering, and product teams to embed AI into existing platforms and deliver new AI-driven capabilities across the organization • Evaluate and adopt modern orchestration frameworks and cloud-native AI tools (such as LangGraph and AWS-based services), while staying current with new AI system design patterns

• Rol de AI Engineer en un importante cliente del sector consumo • Diseñar e implementar agentes conversacionales • Trabajar en la integración con sistemas backend y plataformas de mensajería • Diseñar y optimizar flujos de trabajo basados en IA