Experteer Overview
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As an AI Architect at Kyndryl, you design and implement enterprise-grade AI and Agentic AI architectures that align business objectives with scalable, secure, and maintainable systems. You work with cross-functional teams to translate strategy into practical, trustworthy solutions that deliver measurable value. You influence architecture patterns, governance, and cloud integration while advancing sustainable engineering and responsible AI. This role offers a chance to shape AI-powered platforms at scale within a collaborative, growth-focused culture.
Compensaciones / Ventajas
• Design end-to-end AI and Agentic AI architectures aligned with business goals
• Transform requirements into modular, scalable, and maintainable system designs
• Define architecture patterns for agents, foundation models, data platforms, APIs, integrations, orchestration, observability, security, and cloud infra
• Collaborate with cross-functional teams to meet scalability, performance, resilience, security, and reliability standards
• Contribute to reference architectures, reusable components, design patterns, and technical standards
• Act as a trusted technical partner through solution lifecycle and provide guidance during implementation
• Evaluate emerging AI, data, automation, and cloud technologies to deliver business value
• Ensure AI solutions integrate with existing enterprise systems, data platforms, APIs, and cloud environments
• Champion responsible AI and secure-by-design principles,



embedding governance, privacy, and compliance
• Promote sustainable engineering practices focusing on cost efficiency, model and infrastructure efficiency, and maintainability
• Bridge experimentation and production, evolving AI concepts into enterprise-grade solutions
Responsabilidades
• 3-6 years of experience designing and implementing AI/ML solutions or advanced analytics architectures
• Proven experience integrating AI models into production environments (APIs, microservices, data pipelines)
• Solid understanding of AI/ML architectures and model lifecycle
• Proficiency with cloud ecosystems (Azure, AWS, GCP) and their AI/ML services
• Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow) and container orchestration (Kubernetes, Docker)
• Familiarity with agentic xqbhyrx AI frameworks (LangChain, CrewAI, AutoGen, LlamaIndex) and RAG architectures
• Working knowledge of vector databases, APIs, and integration patterns for intelligent systems
• Understanding of data privacy and regulatory frameworks (GDPR, EU AI Act, Responsible AI principles)
• Bachelor's degree in Computer Engineering, Artificial Intelligence, Data Science, or related field
• Postgraduate studies in AI, Big Data, or Cloud Computing valued
• Cloud architecture certifications and MLOps familiarity are a plus
Requisitos principales
• Be Well programs
• hybrid-friendly culture
• career growth and development
• Certifications with Microsoft, Google, and Amazon
• coaching and hands-on experiences
• supportive environment prioritizing well-being

📌 AI Architect (Madrid)
🏢 Kyndryl
📍 Madrid