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# AI Engineer / AI Solutions Architect

- **Company:** Computer Space
- **Location:** Spain (Remote available)
- **Salary:** €70,000.0 - €100,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Cloud Computing, Python (Programming Language), Salesforce.Com, Apex Code, Genesys, Large Language Models, Generative AI, Backend, Kubernetes, Docker
- **Published:** August 9, 2026
- **Apply:** https://www.jobleads.com/es/job/e9b5dff1ecfee0e9615d9ae229e625571

## About the Role

* Testing, evaluación y observabilidad avanzada de aplicaciones LLM.
 * Arquitecturas escalables y orientadas a producción.
 * Optimización de latencia, costes y calidad de respuesta.
 * Kubernetes, Docker y despliegues cloud-native.
 * Integración de agentes con APIs y sistemas corporativos
 * Genesys (voz y texto): agentes conversacionales, Audio Connector, STT, TTS, gestión de contexto.
 * Salesforce Agentforce: Einstein AI, Flows, Apex, Data Cloud y automatización de procesos.

## Description

* Diseñar y desarrollar agentes de IA generativa con Python u otros lenguajes backend modernos.
 * Construir flujos complejos con frameworks como LangChain y LangGraph.
 * Instrumentar agentes con plataformas de observabilidad LLM (especialmente Langfuse).
 * Diseñar arquitecturas multiagente: planificación, memoria, tool calling, supervisión y coordinación.
 * Implementar soluciones RAG, embeddings y bases vectoriales.
 * Integrar modelos fundacionales (OpenAI, Anthropic, Google…) mediante APIs.
 * Desplegar y operar aplicaciones de IA en cloud (GCP o AWS).
 * Capacidad para diseñar arquitecturas completas de agentes de IA generativa.
 * Visión técnica para seleccionar tecnologías, patrones y herramientas adecuadas.
 * Experiencia llevando agentes a producción con criterios de escalabilidad, mantenibilidad y calidad.
 * Criterio para instrumentar, evaluar y optimizar agentes en entornos reales.
 * LangChain y LangGraph.
 * Langfuse u otras plataformas de observabilidad LLM.
 * Arquitecturas multiagente y orquestación avanzada.
 * RAG, embeddings y bases vectoriales.
 * Integración de modelos fundacionales vía API.


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