Agentic AI Engineer – Mainframe Modernization
Kyndryl (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 28–45 LPA
Posted 15h ago
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Job description
Structured overview of role & requirements
About This Role
- Deploy and scale Agentic AI, code-aware agents and RAG workflows to accelerate mainframe discovery, reverse engineering and modernization.
- Turn legacy application analysis into business rules, dependency maps and architecture artifacts that support refactoring and cloud migration; integrate automation into enterprise tools and CI/CD pipelines.
- Own AI output quality and governance through evaluation frameworks, guardrails and Human-in-the-Loop validation; develop reusable accelerators for modernization teams.
Minimum Requirements
- Work Experience Required: 5–8+ years in software engineering, including 2+ years building and deploying GenAI, LLM or Agentic AI solutions in enterprise production environments.
- Strong AI engineering skills in Agentic AI frameworks and orchestration, Python, prompt/context engineering, RAG, vector databases and related knowledge retrieval systems.
- Hands-on mainframe modernization experience, including application discovery, reverse engineering and code understanding across technologies such as COBOL, PL/I, JCL, CICS, IMS and DB2.
- Experience integrating AI with enterprise tools, repositories and CI/CD pipelines, plus AI evaluation, validation, guardrails, HITL workflows and secure development practices.
Ideal Candidate Profile
- Has worked across both enterprise AI engineering and legacy mainframe transformation, translating code analysis into implementation-ready modernization outputs.
- Can build reusable code-aware agents and automation for transformation, testing and documentation; direct KAF experience is preferred, not stated as mandatory.
- Likely to fit environments requiring rigorous validation of AI-generated code and migration outputs, and close work with mainframe SMEs, architects and cloud teams.