Experteer Overview
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As AI Architect at Kyndryl, you will design and implement end-to-end AI and Agentic AI architectures that translate business goals into scalable, secure systems. You’ll work with diverse teams to deliver enterprise-grade solutions that are intelligent, trustworthy, and Governable. You’ll shape reference architectures, patterns, and standards while evaluating emerging AI technologies to drive measurable business value. This role combines innovation with disciplined engineering to support sustainable, cost-aware AI deployments.
Compensaciones / Ventajas
• Design and implement end-to-end AI and Agentic AI architectures aligned with business objectives
• Translate functional, analytical, and non-functional requirements into modular, scalable designs
• Define architecture patterns for AI agents, foundation models, data platforms, APIs, integration layers, orchestration, observability, security, and cloud infrastructure
• Collaborate with cross-functional teams to ensure scalability, performance, resilience, security, and reliability
• Contribute to reference architectures, reusable components, and technical standards to accelerate AI delivery
• Act as a trusted technical partner through solution lifecycle, guiding implementation and architecture reviews
• Evaluate emerging AI, data, automation and cloud technologies to extract business value




• Ensure AI solutions integrate with existing enterprise systems, data platforms, APIs, and cloud environments
• Champion responsible AI and secure-by-design, embedding governance, privacy, security, and compliance
• Promote sustainable engineering practices focusing on cost efficiency, model and infrastructure efficiency, and maintainability
• Bridge experimentation and production to evolve AI concepts into enterprise-grade solutions
Responsabilidades
• 3-6 years of experience designing and implementing AI/ML solutions or advanced analytics architectures
• 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 AI/ML services
• Hands-on experience with xqbhyrx MLOps tools (MLflow, Kubeflow, Airflow) and container orchestration (Kubernetes, Docker)
• Familiarity with agentic AI frameworks (LangChain, CrewAI, AutoGen, LlamaIndex) and RAG architectures
• Working knowledge of vector databases, APIs, and integration patterns
• Understanding of data privacy and regulatory frameworks (GDPR, EU AI Act, Responsible AI)
Requisitos principales
• Be Well programs supporting financial, mental, physical, and social health
• hybrid-friendly culture
• continuous learning with certifications from Microsoft, Google, and Amazon
• personalized career development and frequent feedback
• access to cutting-edge learning opportunities
• empowerment to grow and contribute to shared success

📌 AI Architect (Barcelona)
🏢 Kyndryl
📍 Barcelona