Join us in shaping the future of financial information. This is a high-leverage, player-coach role at the heart of how we scale AI delivery. You will set the technical direction for production-grade AI solutions. If you are passionate about agentic AI, enjoy solving hard engineering problems, and want to see your work used daily by real users in critical products, this is a unique opportunity to have a tangible impact from day one. What You Will Do Architect Multi-Agent Systems: Design, build, and orchestrate complex agentic workflows using Lang Graph and Lang Chain to handle sophisticated financial queries and agents. Productize AI & Gen AI Solutions: Build the backends, agent/RAG infrastructure, MCP servers, and LLM-serving layers that turn models, prompts, and pipelines into reliable, observable production products. Champion Quality & Coach Peers: Apply clean architecture and proven design patterns, enforce standards through tests and reviews, and coach junior engineers and rotating contributors. Implement Advanced RAG: Build and optimize Retrieval-Augmented Generation systems to ground model responses in proprietary data. Establish Evaluation Pipelines: Create rigorous testing frameworks and metrics to evaluate agent performance, reliability,



and accuracy in a production environment. What You Bring Core AI Engineering Stack: Deep expertise in Python and the modern AI stack, including Lang Chain, Lang Graph, Open AI SDK, and Hugging Face Transformers. Strong ability to debug and optimize multi-agent workflows, with a focus on asynchronous execution, state management, and concurrency. API & Data Proficiency: Experience designing and integrating with complex REST/Graph QL endpoints and handling structured data formats (JSON/XML) for tool calling. Cloud & Dev Ops Mindset: Hands-on experience with containerization (Docker) and cloud platforms (AWS/GCP/Azure) for deploying production-grade AI applications. Quality & Collaboration: Strong testing discipline with pytest, a habit of writing maintainable, well-typed code, and the communication skills to mentor peers and partner closely with data scientists and AI engineers. Experience & Education: 5+ years in software Engineering including significant experience in as a Gen AI Application Developer. A relevant degree in Computer Science or related field is required. #J-18808-Ljbffr

📌 Ai Engineer (Madrid)
🏢 BME | Bolsas y Mercados Españoles
📍 Madrid