Descripción de la oferta
Agentic Engineer (Python, LLM Systems)Si los siguientes requisitos del puesto y la experiencia coinciden con sus habilidades, por favor, asegúrese de enviar su solicitud sin demora. Spain (Barcelona/Madrid preferred) | Hybrid €70k–€120k base + bonus + equityWe’re supporting one of our clients — a fast-scaling, AI-first product company — in hiring an Agentic Engineer to build and scale production-grade LLM agent systems.The RoleOur client is building conversational AI and workflow automation systems powered by multi-step agents. They’re looking for an engineer who understands that shipping AI systems is fundamentally a systems engineering challenge.You’ll work on:- Designing and implementing multi-agent workflows (planning, tool-calling, orchestration)- Building and optimizing RAG pipelines (embeddings, retrieval, context management)- Managing memory strategies (session handling, summarization, vector search)- Developing evaluation and monitoring frameworks for agent quality- Improving latency, reliability, and cost-efficiency of LLM workloads- Ensuring observability and robustness in production environmentsWhat They’re Looking For- Strong backend engineering foundation (Python preferred)- Experience building LLM-powered systems in production- Hands-on work with agents, RAG, embeddings, or orchestration frameworks- Experience with vector databases (Qdrant, Pinecone, Weaviate, etc.)- Cloud-native experience (AWS or similar, containerized services, infra-as-code)- Product mindset — able to ship, iterate, and improve quicklyBonus if you’ve worked on:- Multi-agent systems- Evaluation pipelines or hallucination control- Latency-sensitive AI systems- Scaling conversational AI infrastructureWhat This Role Is Not- Not a pure ML research position- Not a fine-tuning-heavy role- Not just wrapping OpenAI APIsOur client is looking for engineers who have already built real AI systems and want to push them further.Compensation & Setup- €70k–€100k base (flexible for exceptional profiles)- Performance bonus structure- Meaningful equity- Hybrid model (4 in-office days per month)If you’ve already built LLM agents in production and want to go deeper into orchestration, evaluation, and scalable AI systems, we’d love to speak. xcskxlj Apply directly or reach out for a confidential conversation.
