Agentic AI Engineer – Mainframe Modernization
Kyndryl (company site, opens in a new tab)5–8 yrsBengaluruOn-siteDirect career pageEst. 20–40 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 legacy discovery and reverse engineering across mainframe applications.
- Turn AI analysis into modernization deliverables—including business rules, dependency maps, and architecture artifacts—to support refactoring and cloud migration.
- Integrate AI into enterprise tools and CI/CD pipelines, with evaluation, security guardrails, and Human-in-the-Loop validation for production use.
Minimum Requirements
- Work Experience Required: 5–8+ years of software engineering, including 2+ years building and deploying GenAI, LLM, or Agentic AI solutions in enterprise production environments.
- Strong Python skills and hands-on expertise in Agentic AI frameworks, orchestration, prompt/context engineering, RAG, vector databases, and related knowledge systems.
- 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 and development pipelines; expertise in software quality, validation, guardrails, and secure development practices.
Ideal Candidate Profile
- Combines enterprise AI engineering with practical mainframe analysis and can turn code understanding into implementation-ready modernization outputs.
- Has experience validating AI-generated code or migration assets and operating AI workflows in security-sensitive or regulated enterprise settings.
- Direct KAF experience, reusable modernization accelerators, and mentoring cross-functional teams on AI-assisted delivery are preferred signals.