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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** e-dreams - **Location:** Barcelona, Spain (Remote available) - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Code Review, Continuous Integration, Software Debugging, Python (Programming Language), Machine Learning, Management of Software Versions, Cloud Platform System, Chatbots, Large Language Models, Prompt Engineering, Kubernetes, Machine Learning Operations, Software Version Control - **Published:** July 31, 2026 - **Apply:** http://localhost:8888/odigeo-careers/ ## About the Role * Degree in a quantitative or engineering field (Computer Science, Engineering, Mathematics, or related); equivalent hands-on experience also welcome. * Demonstrated experience as an AI Engineer, Ideally, 5+ years as a Data Scientist or Software Engineer. * An excellent production software engineer that understands AI model behavior. Strong Python skills, with solid software engineering fundamentals: APIs, orchestration, observability, measurement, runtime constraints, reliability, production debugging, testing, version control, code review, CI/CD, etc. * Experience building and orchestrating LLM agents and tool use, and a working understanding of prompt engineering and context-window management. * Experience with LLM evaluation methods (LLM-as-judge, human review, model based evals, task-specific datasets…) and production feedback loops plus an instinct for measuring before claiming something works. * Experience with cloud platforms (GCP preferred) and shipping APIs or services into production. * Comfortable working with ambiguity and fast-changing tooling; pragmatic about picking the right level of complexity for the problem. * Written and oral communication skills in English., * Experience fine-tuning or distilling open-weights models; exposure to MLOps/LLMOps tooling (MLflow, Vertex AI, Kubeflow); background in NLP. ## Description As an eDOer, you will have clear objectives, great challenges and a clear overview of how your work contributes to the global company project and its customers. As a Senior AI Engineer in the Data Science team you will be in charge of: * Design, build and ship LLM-powered features (chatbots, agents, RAG-based search, etc) in close collaboration with Data Science, ML Engineering, IT, and Product. * Design LLM applications ranging from pragmatic efficient single-model calls to sophisticated autonomous agents. Use the right frameworks (e.g. LangGraph, Google ADK) to deliver the required agent architecture, manage the underlying LLMs and provide the needed tools and APIs. * Own context engineering as a first-class engineering discipline; treat like code - versioning, testing and evaluating - all model context and configuration. * Work with ML Engineering to deploy AI applications on our cloud platform (GCP), reusing existing MLOps infrastructure where it fits and flagging gaps where it doesn't. * Evaluate, monitor and observe AI features in production and build controls to prevent and minimize model failures and security risks; track model and data drift. Trace model calls, tool usage and agent decisions. Measure costs, latency and build failure safety nets, guardrails and apply security engineering. * Stay current on the fast-moving GenAI landscape and bring back what's worth adopting; share knowledge and best practices across the organisation. ## Related Videos - [Chatbots are going to destroy infrastructures and your cloud bills](https://www.wearedevelopers.com/videos/1130-chatbots-are-going-to-destroy-infrastructures-and-your-cloud-bills) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Are Code Reviews Worth It? Insights from 16 Years of Review Data](https://www.wearedevelopers.com/videos/1135-are-code-reviews-worth-it-insights-from-16-years-of-review-data) - [Three years of putting LLMs into Software - Lessons learned](https://www.wearedevelopers.com/videos/1508-three-years-of-putting-llms-into-software-lessons-learned) - [Testing AI Agents: Automated Evaluation for Chatbots & RAG Systems](https://www.wearedevelopers.com/videos/100300-testing-ai-agents-automated-evaluation-for-chatbots-rag-systems) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai)