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Kyndryl

Managed IT infrastructure and cloud services

Agentic AI Engineer - Mainframe Modernization

AI Application EngineeringPosted on Nov 13
Full-timeNo salary listed

About the Job

Requirements

  • Experience deploying, configuring, integrating, and optimizing enterprise Agentic AI capabilities, orchestration pipelines, custom workflows, and prompt libraries.
  • Expertise in designing code-aware AI agents, Retrieval-Augmented Generation (RAG) pipelines, vector-based knowledge systems, prompt engineering, and context engineering.
  • Hands-on mainframe modernization experience covering legacy application discovery, inventory analysis, and automated reverse engineering across COBOL, PL/I, JCL, CICS, IMS, DB2, and related technologies.
  • Ability to generate application documentation, extract business rules, create dependency maps and architecture artifacts, and convert AI outputs into implementation-ready engineering deliverables.
  • Experience supporting code transformation, refactoring, and migration activities while automating repetitive analysis, mapping, testing, and documentation tasks.
  • Experience integrating AI solutions with enterprise tools, repositories, and development pipelines, and monitoring and improving performance, accuracy, reliability, and scalability.
  • Background in AI quality, validation, and governance, including defining evaluation frameworks, validation mechanisms, guardrails, Human-in-the-Loop workflows, and enterprise security compliance.
  • Collaboration with mainframe subject-matter experts, architects, cloud engineers, and transformation leads, including mentoring teams on AI-assisted delivery practices.
  • 5–8+ years of software engineering experience, including 2+ years building and deploying Generative AI, large language models, and Agentic AI solutions in enterprise production environments.
  • Expertise in Agentic AI frameworks, multi-agent systems, prompt engineering, context engineering, and AI workflow orchestration.
  • Proficiency in Python for workflow automation, REST APIs, SDK integrations, and third-party tool integrations.
  • Experience with Git/GitHub, continuous integration and continuous delivery pipelines, software development lifecycle processes, DevSecOps, and secure development practices.
  • Experience designing AI knowledge systems, including RAG, vector databases, semantic search, embedding models, knowledge graphs, and context retrieval systems.
  • Software quality experience encompassing source code analysis, test automation, quality engineering, and code transformation or developer productivity tools.
  • Knowledge of mainframe modernization, including legacy application discovery, reverse engineering, code understanding, dependency analysis, modernization patterns, and legacy-to-cloud transformation.

Responsibilities

  • Configure and scale KAF, Agentic AI workflows, RAG pipelines, and code-aware agents to accelerate legacy discovery, inventory analysis, and automated reverse engineering across COBOL, PL/I, JCL, CICS, IMS, and DB2.
  • Extract business rules, dependency maps, and architecture artifacts to support code refactoring and cloud migration.
  • Embed AI automation into existing enterprise tools, code repositories, and continuous integration and continuous delivery development pipelines.
  • Establish evaluation frameworks, guardrails, and Human-in-the-Loop validation workflows to ensure output accuracy and enterprise security compliance.
  • Refine prompt and orchestration frameworks, build reusable AI accelerators, and mentor cross-functional modernization teams on AI-assisted delivery.

Desired Qualifications

  • Direct experience working with KAF (Kyndryl Agentic Framework) and contributing reusable AI assets and modernization accelerators across multiple programs.
  • Expertise in validating AI-generated code, test assets, migration outputs, and documentation in regulated or security-sensitive enterprise environments.
  • Track record of identifying recurring modernization challenges and converting them into reusable AI solutions.
  • Experience advancing agent orchestration frameworks and legacy-to-cloud transformation architectures.
  • Experience in code-aware agent development, legacy code context modeling, and mainframe application analysis.
  • Track record implementing automated code transformation and automated test generation solutions.
  • Experience building and scaling enterprise AI platform engineering solutions, multi-agent orchestration platforms, and deep tool/platform integrations.
  • Expertise in AI evaluation frameworks, large language model guardrails and governance, generated code validation, and Human-in-the-Loop workflows.

About the Company

Kyndryl

Managed IT infrastructure and cloud services

Kyndryl provides managed IT infrastructure services for large enterprises, helping them run and modernize their technology environments. Its offerings cover cloud adoption, cybersecurity, security operations, and digital workplace services, all delivered under long-term managed-service contracts. The company works by partnering with major technology providers (including Microsoft) to offer integrated, end-to-end solutions, often complemented by a new security operations center (SOC) and other security capabilities. This focus sets it apart from competitors through scale, enterprise-grade governance, and a history rooted in IBM’s infrastructure services, now independent but aligned with large technology partners. The goal is to support digital transformation by providing reliable, scalable, and secure infrastructure management that enables enterprises to operate efficiently and securely in a cloud-enabled world.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
2021

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