
Staff 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 (e.g., conversational bots, AI-powered search, unstructured data processing, GenBI) that are reusable and scalable across the enterprise.
- Lead architectural decisions, bringing standard methodologies in software development lifecycle, explain ability, and responsible AI.
- Lead multi-functional team initiatives—embedded projects with business stakeholders—to rapidly build and deploy AI solutions that solve high-priority problems.
- Evaluate and integrate existing AI tools, frameworks, and APIs (e.g., LLMs, vector DBs, retrieval-augmented generation) into robust applications.
- Champion automation in workflows—from data ingestion and preprocessing to model integration and deployment. Define their success criteria, metrics and Standard operation procedures.
- Partner with data scientists, product managers, and other engineers to ensure end-to-end delivery and reliability of AI products.
- Know the latest 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 engineering practices across the organization.
- Mentor other engineer and data scientists and provide technical leadership across projects, helping set the standard for rigor and impact
- 7+ 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.
- Solid 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.).
- Experience with large language models (LLMs), vector-based search, retrieval-Augmented generation (RAG), or unstructured data processing.
- Ability to move quickly while maintaining code quality, test coverage, and operational excellence.
- Strong problem-solving skills and a bias for action, with the ability to navigate ambiguity and lead through complexity.
- Strong experience with technical mentorship and cross-team influence.
- Ability to translate sophisticated technical ideas into clear business insights and communicate effectively with multi-functional partners
- Familiarity with AI/ML tools such as LangChain, Haystack, Hugging Face, Weaviate, or similar ecosystems.
- Experience using GenAI frameworks such as LlamaIndex, Crew AI, AutoGen, or similar agentic/LLM orchestration toolkits.
- Experience building reusable modeling components or giving to internal ML platforms.
- Background in working with embedded teams or in forward-deployed environments where rapid iteration and close business collaboration are key.
- Proficiency in Python and common ML/data science libraries (e.g., scikit-learn, pandas, NumPy, PyTorch, TensorFlow).
- Solid knowledge of machine learning fundamentals, including supervised and Unsupervised learning, model evaluation, and statistical inference.
- 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.