Responsibilities

Own end-to-end delivery for complex AI engagements
Translate business challenges into technical solutions, lead solution design and deployment
Operate as a trusted technical partner to customers
Own delivery end-to-end, from scoping to production
Troubleshoot and enhance system performance, scalability, and reliability
Capture deployment learnings, document best practices, and proactively share insights
Adapt quickly to emerging technologies and evolving customer requirements
Actively contribute to the evolution of Kyndryl’s AI platforms

Requirements

Demonstrable expertise in Python (or another modern language such as C#, Node.js or TypeScript)
Experience working with AI/ML frameworks like TensorFlow or PyTorch is a plus
Solid grasp of the software delivery lifecycle, version control (Git & GitHub), and data engineering tools such as Pandas and Spark
Experience with cloud AI platforms (AWS, Azure, Google AI) and distributed computing architectures
Familiarity with community-driven AI tools and libraries, including Hugging Face




Deep technical expertise in one or two domains, with broad understanding across AI/ML, cloud, and consulting
Experience designing, building, or integrating multi-agent systems and orchestration frameworks
Practical knowledge of deploying RAG architectures and integrating structured and unstructured knowledge sources into AI solutions
Knowledge of system-level optimisation and security best practices for scalable AI systems
Ability to translate business requirements into technical solutions and communicate technical value to diverse stakeholders
Willingness to travel and work on customer premises as required

Core Competencies
Demonstrates expertise in Python and AI/ML frameworks, with a strong understanding of the software delivery lifecycle and cloud AI platforms. Capable of translating business challenges into technical solutions while ensuring system performance and scalability.
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📌 Lead Agentic, AI Architect (Madrid)
🏢 Jobtailor
📍 Madrid