Lead Agentic & Ai Architect (Fde) At Kyndryl

As a Forward Deployed Engineer (FDE) at Kyndryl, you own end-to-end delivery for complex AI engagements, translating business challenges into technical solutions.ResponsibilitiesPartner with customers to understand business challenges and translate them into high?quality, fit?for?purpose technical solutions, prioritising the right outcome over the fastest one.Build and iterate custom AI solutions tailored to customer needs, leveraging agentic AI frameworks.Own delivery end to end, from scoping to production, working as part of the customer team to engineer and deploy production?ready solutions that drive adoption and measurable business outcomes.Diagnose and enhance system performance, scalability, and reliability.Capture deployment learnings, document best practices, and share insights to improve Kyndryl’s core platforms and frameworks.Adapt quickly to emerging technologies and evolving customer requirements by engaging in ongoing professional development.Contribute to the evolution of Kyndryl’s AI platforms through feedback, code contributions, and collaboration with product teams.Required Skills and ExperienceDemonstrable expertise in Python (or another modern language such as C#, Node.js or TypeScript); experience 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.Preferred Skills and ExperienceFamiliarity with community-driven AI tools and libraries, including Hugging Face and relevant repositories.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 (e.g., LangGraph, Semantic Kernel, Agent Framework, AutoGen, CrewAI), including the development of agent protocols and coordination mechanisms.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, including executive audiences.Willingness to travel and work on customer premises as required.xcskxljEducationDegree?level qualification in Computer Science, Informatics, Data Science, Engineering, or a closely related discipline - or equivalent professional experience.#J-*****-Ljbffr

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. Preferred Skills and ExperienceFamiliarity with community-driven AI tools and libraries, including Hugging Face and relevant repositories. 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 (e.g., LangGraph, Semantic Kernel, Agent Framework, AutoGen, CrewAI), including the development of agent protocols and coordination mechanisms. 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, including executive audiences. Willingness to travel and work on customer premises as required. xcskxlj EducationDegree?level qualification in Computer Science, Informatics, Data Science, Engineering, or a closely related discipline - or equivalent professional experience. #J-*****-Ljbffr

As a Forward Deployed Engineer (FDE) at Kyndryl, you own end-to-end delivery for complex AI engagements, translating business challenges into technical solutions. ResponsibilitiesPartner with customers to understand business challenges and translate them into high?quality, fit?for?purpose technical solutions, prioritising the right outcome over the fastest one. Build and iterate custom AI solutions tailored to customer needs, leveraging agentic AI frameworks. Own delivery end to end, from scoping to production, working as part of the customer team to engineer and deploy production?ready solutions that drive adoption and measurable business outcomes. Diagnose and enhance system performance, scalability, and reliability. Capture deployment learnings, document best practices, and share insights to improve Kyndryl’s core platforms and frameworks. Adapt quickly to emerging technologies and evolving customer requirements by engaging in ongoing professional development. Contribute to the evolution of Kyndryl’s AI platforms through feedback, code contributions, and collaboration with product teams.