Senior AI Engineer (Generative AI) — Google Cloud Platform

• Key role within the Data & AI area, in the generative AI line on Google Cloud.
• Challenging projects of generative AI in production with top-tier clients.
• Training budget and support for certifications.
• Advanced technical environment and a community of practice.
• Hybrid model (office in Madrid + flexibility) and occasional travel.
• Competitive compensation package commensurate with experience.

We are looking for a senior AI Engineer specialized in generative AI with a practical mindset and results orientation: someone who does not stop at the prototype, but builds LLM-based applications (RAG, agents, and multi-agent systems) on GCP and takes them to production with measurable quality, security, and traceability. If you are motivated by an AI solution that truly works in the hands of real users—and furthermore, you want to contribute to the technical evolution of the area—this position is for you.

You will work as a technical reference for generative AI on high-impact projects with top-tier clients, working in close collaboration with data architects, data engineers, developers, and platform engineers. Hybrid position in Madrid with occasional travel.

• You will design and develop LLM-based applications: RAG solutions, agents, and multi-agent systems with Gemini in Vertex AI, from structured information extraction to content generation.
• You will build robust retrieval systems: you will define chunking, embeddings, hybrid search, and reranking strategies, and you will measure their quality with data.
• You will define how models are evaluated and improved: evaluation datasets, quality and groundedness metrics, and automated regression tests in CI.
• You will take solutions to production: deployment with Docker and CI/CD, prompt and configuration versioning, and agent observability (traces, cost, and latency).
• You will guarantee the security of AI solutions: protection against prompt injection, guardrails on outputs, and least privilege in tools.
• You will collaborate with the business and the client: you will translate real problems into AI solutions and work with domain experts to convert their criteria into test cases.
• You will contribute to pre-sales and proposals: you will prepare technical estimates, architectures for RFP/RFI, and participate in demos and PoCs with clients.
• You will promote continuous improvement and technological evolution: you will propose cost/performance optimizations (FinOps in BigQuery/Dataflow), and introduce reusable patterns and best practices to the area.

• Rigor with quality: you do not take a model response for granted without measuring it, and you know how to explain why a system works or fails.
• Autonomy and technical judgment: you make decisions within your scope, justify them, and document them.
• Communication with non-technical profiles: you understand what a correct response means for the business and translate it into verifiable requirements.
• Customer orientation: you anticipate needs and prioritize real impact over technological novelty.
• Pragmatic mindset: you choose the simplest solution that solves the problem and can be operated.
• Collaboration and knowledge sharing: you share learnings, document, and help the team grow.