Agentic AI Engineer – Mainframe Modernization

Responsibilities

You will deploy and scale Agentic AI workflows and RAG pipelines to modernize legacy mainframe applications. Additionally, you will integrate AI automation into enterprise CI/CD pipelines while establishing governance and validation frameworks for production-ready outcomes.

Requirements

The role requires 5-8+ years of software engineering experience with at least 2 years focused on GenAI, LLMs, and Agentic AI solutions. Candidates must possess strong expertise in Python, mainframe technologies like COBOL and DB2, and experience with modern DevOps practices.

Skills

• Agentic AI
• Mainframe Modernization
• Python
• RAG
• LLM
• Prompt Engineering
• COBOL
• CI/CD
• Git
• DevSecOps
• Vector Databases
• Workflow Orchestration
• API Development
• Software Engineering
• Cloud Migration
• Code Refactoring

Benefits

• Flexible work environment
• Supportive environment
• Well-being programs
• Learning opportunities
• Professional development
• Certification support

About this role

Who We Are
At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world’s leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people—Kyndryls—that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive.

The Role
Your Role:

You will be an AI & Mainframe Modernization Engineer deploying and scaling KAF and Agentic AI capabilities to accelerate legacy enterprise transformations. Working alongside mainframe SMEs, architects, and cloud teams, you will build code-aware AI workflows, automate reverse engineering and refactoring, and enforce validation guardrails to deliver production-ready modernization outcomes.
What You Will Do:
Deploy & Optimize AI Workflows: 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.
Drive Code Transformation: Extract business rules, dependency maps, and architecture artifacts to support code refactoring and cloud migration.
Integrate into Enterprise Pipelines: Embed AI automation directly into existing enterprise tools, code repositories, and CI/CD development pipelines.
Enforce Governance & Quality: Establish evaluation frameworks, guardrails, and Human-in-the-Loop (HITL) validation workflows to ensure output accuracy and enterprise security compliance.
Scale & Mentor: Continuously refine prompt and orchestration frameworks, build reusable AI accelerators, and mentor cross-functional modernization teams on AI-assisted delivery.
Required Qualifications:
Experience deploying, configuring, integrating, and optimizing enterprise Agentic AI capabilities, orchestration pipelines, custom workflows, and prompt libraries.
Strong AI engineering 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 background covering legacy application discovery, inventory analysis, and automated reverse engineering across COBOL, PL/I, JCL, CICS, IMS, DB2, and related technologies.
Demonstrated ability to generate application documentation, business rules extraction, dependency maps, and architecture artifacts, converting AI outputs into implementation-ready engineering deliverables.
Practical experience supporting code transformation, refactoring, and migration activities while automating repetitive tasks across analysis, mapping, testing, and documentation generation.
Proven ability to integrate AI solutions with enterprise tools, repositories, and development pipelines while monitoring and improving performance, accuracy, reliability, and scalability.
Strong background in AI quality, validation, and governance—including defining evaluation frameworks, validation mechanisms, guardrails, Human-in-the-Loop (HITL) workflows, and enterprise security compliance.
Proven collaboration skills with Mainframe SMEs, Architects, Cloud Engineers, and Transformation Leads, including mentoring teams on AI-assisted delivery best practices.
Preferred Qualifications:
Direct experience working with KAF (Kyndryl Agentic Framework) and contributing to reusable AI assets and modernization accelerators across multiple programs.
Deep expertise in validating AI-generated code, test assets, migration outputs, and documentation within 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.

Your Future at Kyndryl:
Every position at Kyndryl offers a way forward to grow your career. We have opportunities that you won’t find anywhere else, including hands-on experience, learning opportunities, and the chance to certify in all four major platforms. Whether you want to broaden your knowledge base or narrow your scope and specialize in a specific sector, you can find your opportunity here.

Who You Are
You’re good at what you do and possess the required experience to prove it. However, equally as important ,you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused , someone who prioritizes customer success in their work. And finally, you’re open and borderless , naturally inclusive in how you work with others.

Required Qualifications:
5-8+ years of software engineering experience, including 2+ years of hands-on experience building and deploying GenAI, Large Language Models (LLMs), and Agentic AI solutions into enterprise production environments.
Deep expertise in AI & Agentic Engineering, covering Agentic AI Frameworks, Multi-Agent Systems, Prompt Engineering, Context Engineering, and AI Workflow Orchestration.
Strong proficiency in Python for developing workflow automation, REST APIs, SDK integrations, and third-party tool integrations.
Hands-on experience with Git/GitHub, CI/CD pipelines, SDLC processes, DevSecOps, and secure development practices.
Proven experience designing AI Knowledge Systems, including Retrieval-Augmented Generation (RAG), Vector Databases, Semantic Search, Embedding Models, Knowledge Graphs, and Context Retrieval Systems.
Strong software quality background encompassing source code analysis, test automation, quality engineering, and working with code transformation or developer productivity tools.
Solid knowledge of Mainframe Modernization, including legacy application discovery, reverse engineering, code understanding, dependency analysis, modernization patterns, and legacy-to-cloud transformation.
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About Kyndryl

IT Services and IT Consulting · 10,001+ employees · headquartered in New York City, New York