Lead Agentic, AI Architect

Responsibilities

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• 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

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• 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. xcskxlj Capable of translating business challenges into technical solutions while ensuring system performance and scalability.

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