Agentic AI Engineer – Mainframe Modernization
Kyndryl (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 22–40 LPA
Posted 15h ago
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Job description
Structured overview of role & requirements
About This Role
- Deploy and scale Agentic AI, RAG and code-aware workflows for mainframe discovery, reverse engineering and legacy modernization.
- Turn AI analysis into engineering deliverables—including business rules, dependency maps and architecture artifacts—to support refactoring and cloud migration; integrate workflows into enterprise tools, repositories and CI/CD pipelines.
- Own AI quality and governance through evaluation frameworks, guardrails and Human-in-the-Loop validation; develop reusable accelerators and mentor 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 experience with agentic frameworks and orchestration, prompt/context engineering, RAG, vector databases or related knowledge systems; proficiency in Python, REST APIs and integrations.
- Hands-on mainframe modernization experience covering legacy discovery, reverse engineering and dependency analysis across technologies such as COBOL, PL/I, JCL, CICS, IMS and DB2.
- Experience with Git/GitHub, CI/CD, SDLC and secure development, plus software quality, code analysis or test automation and AI output validation/governance.
Ideal Candidate Profile
- Has combined enterprise AI delivery with practical mainframe analysis and can convert code-aware AI outputs into usable modernization artifacts and transformation support.
- Can integrate and scale AI workflows within existing engineering environments while balancing automation with evaluation, security controls and human validation.
- KAF experience, reusable modernization accelerators, automated code transformation or test generation, and work in regulated or security-sensitive environments are preferred signals.