We have a relentless passion for quality and a drive to keep ahead of the competition. As a Wealthtech, Allfunds blends our wealth management expertise with the innovation and creativity of a fintech. We have over €1.7 trillion assets under administration and are the leading B2B platforms for the fund industry. We built and continue to evolve a digital ecosystem that covers the entire fund distribution value chain and investment cycle, with solutions including dealing and execution, data analytics, regulatory solutions, ESG tools, blockchain, and alternative investments.
Founded in Madrid in 2000, Allfunds offers international opportunities, a commitment to work-life balance, competitive benefits packages including adaptable holidays, and continued training and development. This is under-pinned by our values to have a positive social impact on the markets in which operate.
Allfunds. is achieving this through a deep commitment to quality and outstanding human capital, by providing the best service for our clients, and by creating value for all our stakeholders. We believe that our people’s talent is what creates our world-class service. So, our clients, employees, and partners can count on us for the best services.
The role is responsible for transforming business challenges into scalable AI architectures, selecting the appropriate technologies, models, frameworks, and cloud services to deliver measurable business value.
Working closely with business stakeholders, product owners, data scientists, software engineers, and enterprise architects, the AI Architect designs end-to-end solutions based on Large Language Models (LLMs), Machine Learning, Deep Learning, Retrieval-Augmented Generation (RAG), AI Agents, and Intelligent Automation capabilities.
The AI Architect defines architectural standards and best practices for the development of enterprise AI applications that integrate with APIs, data platforms, cloud-native services, and existing business systems.




The AI Architect is responsible for evaluating AI models and technologies, establishing governance frameworks, ensuring AI security and compliance, and defining monitoring, observability, and operational controls for production environments. The role also provides technical leadership throughout the entire AI solution lifecycle, from ideation and architecture through implementation and deployment.
Define enterprise AI architecture principles, standards, and best practices.
Define end-to-end solution architectures including model orchestration, agent workflows, retrieval mechanisms, prompt engineering, and tool integration.
Design scalable and secure AI platforms on public cloud providers (Azure, AWS, or GCP).
Establish governance, security, compliance, and Responsible AI controls.
Evaluate foundation models, embeddings, vector databases, AI frameworks, and cloud AI services.
Define observability, monitoring, model evaluation, and operational processes for AI workloads.
Ensure AI solutions are aligned with enterprise architecture, cybersecurity, and data governance requirements.
Strong knowledge of Large Language Models (LLMs) and Generative AI architectures.
Experience designing solutions using OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or similar foundation models.
Deep understanding of Machine Learning and Deep Learning concepts and architectures.
Strong Python development skills.
Experience building and consuming REST APIs and event-driven architectures.
Knowledge of vector databases, embeddings, RAG architectures, and semantic search.
Experience with cloud platforms such as Azure, AWS, or GCP .
Understanding of MLOps, LLMOps, CI/CD, and AI deployment best practices.
Experience with AI Agent platforms such as Microsoft Copilot Studio, CrewAI, AutoGen, Semantic Kernel, or similar frameworks.
Experience with Kubernetes, Docker, and cloud-native architectures.
Knowledge of data engineering, data lakes, and enterprise integration patterns.

📌 Architect AWS Cloud (Madrid)
🏢 ALLFUNDS
📍 Madrid