Director / AI Architecture / Generative & Agentic AI

We are looking for an AI Architecture Director | Generative & Agentic AI to join our Product practice in Madrid.

The selected person will lead transformation initiatives based on Artificial Intelligence, Generative AI, and Agentic AI for large organizations in sectors such as Consumer, Retail, Travel, Industrial, Construction, and Life Sciences, among others.

We are looking for a profile that combines enterprise architecture, strategic vision, and executive communication skills with knowledge of Agentic AI architectures, AI context design for agents, and the reinvention of technological processes through AI.

• Lead transformation programs through AI, Generative AI, and Agentic AI for large clients, identifying use cases, defining target architectures and operating models, and taking initiatives from strategy through to implementation and scaling.

• Design enterprise AI architectures that integrate cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform; Large Language Models (LLM); AI agents; corporate systems; data platforms; and integration, governance, and security mechanisms.

• Design and build context architectures and databases for AI that allow LLMs and agents to access, retrieve, and exploit business information in a structured manner, including contextualization patterns and information retrieval for solutions based on models such as GPT, Claude, and equivalents.

• Define architectures and methodologies to apply Agentic AI in the technology area, including the Technology Development Life Cycle (TDLC), demand management, functional analysis, and other technological processes, establishing differentiated patterns and capabilities at the corporate, departmental, and project levels.

• Define enterprise architectures for Agentic AI and Generative AI aligned with business objectives, technological architecture, and the governance requirements of large organizations.

• Design the architecture necessary to deploy Agentic AI capabilities, including LLMs, agents, orchestration, context layers, information retrieval systems, integrations with enterprise systems, data platforms, and cloud services.

• Define the architectural model of the agentic TDLC, identifying which components, services, and capabilities should be established as reusable corporate platforms, which correspond to the departmental scope, and which must be designed specifically for each project.

• Design context architectures that allow AI agents and models to exploit business knowledge and data from multiple sources, considering patterns such as Retrieval-Augmented Generation (RAG), semantic search, vectorization, and context management.

• Apply Agentic AI to technology area processes beyond software development, including demand management, functional analysis, architecture, engineering, testing, operation, and maintenance.

• Apply process reinvention methodologies to identify activities susceptible to being transformed through AI agents, redesign workflows, and define new interaction models between people, agents, and corporate systems.

• Evaluate and select AI platforms, LLMs, cloud services, data platforms, and technological ecosystems suitable for complex enterprise environments.

• Define AI operating models, adoption strategies, and governance, security, Responsible AI, and scalability mechanisms.

• Build AI business cases quantifying costs, benefits, operational efficiency, return on investment, and initiative prioritization.

• Lead multidisciplinary teams composed of architects, consultants, data specialists, and AI engineers.

• Present architectures, roadmaps, transformation proposals, and business cases to CIOs, CTOs, CDOs, and other executive stakeholders.

• Contribute to commercial growth by identifying opportunities and developing value propositions for AI Transformation, Generative AI, and Agentic AI.