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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Artificial Intelligence Consultant - **Company:** Virtusa - **Location:** Madrid, Spain - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Continuous Integration, Information Engineering, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Pytorch, Large Language Models, IT Architecture, HybridCloud, AI Platforms, Kubernetes, Machine Learning Operations, Databricks - **Published:** August 8, 2026 - **Apply:** https://www.buscojobs.com.es/artificial-intelligence-consultant-en-madrid-ID-365957800 ## About the Role Enterprise Architecture experience: proven EA leadership translating concepts into- Hands-on AI/ML engineering: building, fine-tuning, and deploying ML/DL models (LLMs, RAG, MLOps) in production. - AI platforms: hands-on with AWS (Bedrock, SageMaker, Amazon Q), Azure (Azure AI, ML, OpenAI), and Databricks. - Engineering and analytics: strong Python, TensorFlow/PyTorch, containers, Kubernetes, and CI/CD for hybrid cloud. - Data modelling and governance: conceptual/logical modelling and governance standards in regulated environments. - Architecture judgement: select fit-for-purpose AI architecture per use case, with full-lifecycle- Leadership: lead a small team of AI architects and help shape enterprise AI strategy and direction. - Degree in data science, AI engineering, or a related field (or equivalent experience). - Postgraduate degree in MIS, AI, data science, or a related field. - Recognised thought leader in applying AI within the enterprise and across the industry. - Extensive senior AI, data science, data engineering, and AI architecture experience delivering- Hands-on building AI models, including LLMs and LVMs, across diverse data types#J-*****-Ljbffr ## Description Enterprise Architecture experience: proven EA leadership translating concepts into- Hands-on AI/ML engineering: building, fine-tuning, and deploying ML/DL models (LLMs, RAG, MLOps) in production.- AI platforms: hands-on with AWS (Bedrock, SageMaker, Amazon Q), Azure (Azure AI, ML, OpenAI), and Databricks.- Engineering and analytics: strong Python, TensorFlow/PyTorch, containers, Kubernetes, and CI/CD for hybrid cloud.- Data modelling and governance: conceptual/logical modelling and governance standards in regulated environments.- Architecture judgement: select fit-for-purpose AI architecture per use case, with full-lifecycle- Leadership: lead a small team of AI architects and help shape enterprise AI strategy and direction.- Degree in data science, AI engineering, or a related field (or equivalent experience).- Postgraduate degree in MIS, AI, data science, or a related field.- Recognised thought leader in applying AI within the enterprise and across the industry.- Extensive senior AI, data science, data engineering, and AI architecture experience delivering- Hands-on building AI models, including LLMs and LVMs, across diverse data types#J-*****-Ljbffr ## Related Videos - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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