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