Applied AI Engineer
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Job Description
Applied AI Engineer responsible for designing and building AI systems for logistics solutions in LATAM. Collaborate across teams to translate ambiguous problems into measurable, maintainable solutions.
Responsibilities:
- Diseñar y construir sistemas de IA en producción que resuelven problemas reales de negocio, end-to-end: desde discovery hasta operación.
- Trabajar con producto y operaciones para traducir problemas ambiguos en soluciones acotadas, medibles y mantenibles.
- Construir pipelines de datos que alimentan tanto modelos como superficies de producto.
- Diseñar sistemas de evaluación rigurosos: cómo medimos calidad, cómo detectamos regresiones, cómo decidimos cuándo algo está listo para shippear.
- Integrar LLMs en producción con todos los retos que eso implica: prompt engineering serio, tool use, manejo de costos y latencia, control de calidad de outputs.
- Tomar decisiones técnicas sobre qué tipo de solución aplicar a cada problema. No todo necesita un LLM, no todo necesita ML, y parte del rol es saber distinguir.
- Diseñar e implementar las salvaguardas de seguridad del sistema: límites de autonomía, aprobaciones humanas, aislamiento entre clientes, auditoría.
- Colaborar con el equipo de backend para definir contratos e integraciones limpias entre servicios.
- Mentorear a otros ingenieros en prácticas de IA aplicada conforme el equipo crezca (responsabilidad creciente con el nivel de seniority).
Requirements:
- Inglés B2 o superior.
- +4 años de experiencia en ingeniería de software, con al menos 2 años trabajando en sistemas de Machine Le producción (noarning o IA en solo notebooks o POCs).
- Experiencia práctica construyendo sistemas con LLMs en producción: prompt engineering serio, function calling / tool use, RAG, manejo de costos y latencia, evaluación de outputs.
- Sólido conocimiento de al menos un lenguaje fuerte para sistemas de IA — Python es el más común, pero también consideramos perfiles fuertes en Go, Rust o TypeScript/Node siempre que tengas experiencia construyendo sistemas de ML/IA productivos en ese stack.
- Experiencia con al menos un framework de ML (PyTorch, scikit-learn, JAX, o equivalente).
- Capacidad de tomar un problema de producto ambiguo y traducirlo en un sistema de IA acotado, medible y mantenible.
- Mentalidad de evaluación primero: sabes que un sistema de IA sin métricas no es un sistema, es una apuesta.
- Capacidad para comunicar trade-offs técnicos a audiencias técnicas y no técnicas, en español e inglés.
- **A considerar:**
- Experiencia con Ruby on Rails — parte de nuestro stack convive con backend en Rails, y poder leer/escribir código del backend acelera tu trabajo.
- Experiencia profunda con APIs de algún proveedor comercial de LLMs en producción.
- Experiencia construyendo agentes con tool-use loops en producción (no solo demos).
- Experiencia con sistemas multi-tenant y los trade-offs de seguridad asociados.
- Experiencia en logística, fintech, o cualquier dominio donde las decisiones de la IA tienen consecuencias monetarias o legales — donde "alucinar" no es una opción aceptable.
- Contribuciones a proyectos open source de IA/ML.
- Experiencia con cloud providers (GCP, AWS, Azure) y herramientas de contenerización (Docker, Kubernetes).
- Experiencia con sistemas de mensajería event-driven (Kafka, Pub/Sub, o similar).
Benefits:
- Misión a nivel regional: lograr que los negocios de LATAM se despreocupen de su logística.
- Ubicación: Argentina, Colombia, México, Venezuela, Panamá, Perú.
- Esquema: 100% remoto.
- Horario: Lunes a Viernes 8:00 a 17:00 CST (México).
- Con flexibilidad de horario cuando haya nuevos releases.
- Crecimiento y desarrollo profesional.
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