
Senior AI Engineer
- Madrid
- Permanente
- Tiempo completo
- Design, develop, and maintain production-grade AI applications and services using modern software engineering practices (CI/CD, testing, observability, cloud-native design).
- Define and implement foundational platforms and tools (e.g., conversational bots, AI-powered search, unstructured data processing, GenBI) that are reusable and scalable across the enterprise.
- Participate in cross functional team initiatives—embedded projects with business stakeholders—to rapidly build and deploy AI solutions that tackle high-priority business problems.
- Evaluate and integrate existing AI tools, frameworks, and APIs (e.g., LLMs, vector DBs, retrieval-augmented generation, AI agents) into robust applications.
- Champion automation in workflows—from data management ingestion and preprocessing to evaluation, to model integration and deployment.
- Collaborate with data scientists, product managers, and other engineers to ensure end-to-end delivery and reliability of AI products.
- Stay current with emerging AI technologies, but prioritize practical application and delivery over experimental research.
- Chip in to the internal knowledge base, tooling libraries, and documentation to scale AI engineering standard methodologies across the organization.
- 5+ years of professional software engineering experience; ability to independently design and ship sophisticated systems in production.
- Strong programming skills in Python (preferred), Java, or similar languages, with experience in developing microservices, APIs, and backend systems.
- Strong problem-solving skills and the ability to balance engineering rigor with delivery speed.
- Confirmed understanding of software architecture, cloud infrastructure (AWS, Azure, or GCP), and modern DevOps practices.
- Experience integrating machine learning models into production systems (e.g., LLMs via APIs, fine-tuning, RAG patterns, embeddings, agents and crew of agents etc.).
- Ability to move quickly while maintaining code quality, test coverage, and operational excellence .
- Familiarity with AI/ML tools such as LangChain, Haystack, Hugging Face, Weaviate, or similar ecosystems.
- Hands-on experience with Retrieval Augmented Generation applications, AI agents and systems built around them.
- Experience using GenAI frameworks such as LlamaIndex, Crew AI, AutoGen, or similar agentic/LLM orchestration toolkits.
- Exposure to working with unstructured data (documents, conversations, images) and transforming it into usable structured formats.
- Experience building chatbots, search systems, or generative AI interfaces.
- Background in working within platform engineering or internal developer tools teams.
- Prior experience working in an embedded (forward-deployed) team model with business stakeholders.
- Experience building production grade, reliable AI applications