• You’ll work at the intersection of product engineering and ML engineering. • Our mission is to create the platform that enables building accurate and reliable AI agents, delivering an outstanding experience to our internal Ops team for the creation, iteration and monitoring of their agents, without requiring hard technical skills. • You'll implement new capabilities for AI agents, as well as tooling to make ops autonomous on the creation, evolution, monitoring and evaluation of their agents. • You'll work on making our system scale, going from a few dozen to tens of thousands of tasks automated daily. • You'll have significant influence on system architecture and code quality. • You'll mentor engineers, contribute to our product & engineering culture, and help build the team (including participating in hiring).

• Lead the architecture, development, training, optimization, and deployment of AI/ML models and pipelines from prototype to production scale. • Develop cloud-based AI services (leveraging LLMs and multimodal models via APIs like Gemini, OpenAI, or equivalents) for advanced personalization, recommendation engines, natural language understanding of travel queries, and feedback loops. • Establish and enforce best practices: clean ML code, experiment tracking, MLOps (model versioning, monitoring, A/B testing, drift detection), automated evaluation pipelines, cost-efficient inference, and ethical AI considerations (bias mitigation, privacy). • Collaborate on feature definition, data requirements, success metrics, and iteration. • Handle unique challenges in an AI-powered travel app: multimodal data (location, text, images), sparse/seasonal travel datasets, real-time adaptability, offline/online hybrid inference, and seamless integration with mobile clients and backend APIs. • Mentor future team members as we expand the AI engineering group and help shape our AI culture from the start.

• Architect and build agentic AI systems using Claude Code • Design the AI harness, including: - State management - Context management (preventing context rot) - Tool orchestration - Error recovery strategies - Verification and validation loops - Failure reflection and learning • Define SOPs and system logic before building agents • Apply context engineering (ACE) so AI receives only what it needs — no more, no less • Convert non-binary business problems into binary, measurable questions • Ensure continuous improvement, performance tracking, and cost optimization • Act as the bridge between product vision and technical execution

• Diseño e implementación de soluciones impulsadas por IA para optimizar procesos de Backoffice. • Identificar, priorizar y ejecutar casos de uso de IA y automatización con impacto empresarial. • Desarrollar, desplegar y mantener modelos de IA, flujos de trabajo inteligentes y soluciones de automatización. • Integrar soluciones de IA con sistemas empresariales (ERP, CRM, ITSM, plataformas de datos). • Trabajar con fuentes de datos estructuradas y no estructuradas para habilitar insights impulsados por IA. • Asegurar que las soluciones de IA cumplan con los estándares de seguridad, privacidad y gobernanza. • Colaborar con interesados para traducir necesidades empresariales en soluciones técnicas. • Apoyar la adopción a través de documentación y mejores prácticas.