Agentic AI Engineer – Mainframe Modernization
Kyndryl (company site, opens in a new tab)5–8 yrsBengaluruOn-siteDirect career pageEst. 20–35 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 for mainframe discovery, inventory analysis and reverse engineering.
- Turn AI-generated business rules, dependency maps and architecture insights into support for code refactoring and legacy-to-cloud migration.
- Integrate workflows into enterprise tools and CI/CD pipelines; establish evaluation, security guardrails and human validation to ensure reliable outputs.
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 expertise in Agentic AI frameworks, multi-agent orchestration, prompt/context engineering, RAG, vector databases and AI knowledge systems; proficiency in Python, REST APIs and SDK integrations.
- Hands-on mainframe modernization experience, including legacy discovery and reverse engineering across COBOL, PL/I, JCL, CICS, IMS and DB2.
- Experience integrating AI with enterprise tools, repositories and CI/CD; knowledge of secure SDLC/DevSecOps, software quality and testing, plus AI evaluation, guardrails and human-in-the-loop validation.
Ideal Candidate Profile
- Combines production AI engineering with practical mainframe analysis and can translate legacy-code insights into implementation-ready modernization outputs.
- Has worked across mainframe SMEs, architects and cloud teams, embedding automation into existing engineering pipelines rather than delivering standalone prototypes.
- Candidates with KAF experience, reusable modernization accelerators, and validation of AI-generated code or migration outputs are especially aligned.