Agentic AI Engineer – Mainframe Modernization
Kyndryl (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 18–30 LPA
Posted 15h ago
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Job description
Structured overview of role & requirements
About This Role
- Deploy and scale enterprise Agentic AI, code-aware agents, and RAG workflows for mainframe discovery, reverse engineering, refactoring, and cloud migration.
- Turn legacy code analysis into implementation-ready business rules, dependency maps, and architecture artifacts; integrate automation into enterprise tools, repositories, and CI/CD pipelines.
- Own AI quality and governance through evaluation frameworks, guardrails, security controls, and Human-in-the-Loop validation; develop reusable modernization accelerators.
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 expertise in agent frameworks/orchestration, prompt and context engineering, RAG, vector databases, semantic search, embeddings, and knowledge systems.
- Hands-on mainframe modernization experience, including discovery, reverse engineering, code understanding, and dependency analysis across technologies such as COBOL, PL/I, JCL, CICS, IMS, and DB2.
- Proficiency in Python, REST APIs and integrations, plus Git/GitHub, CI/CD, SDLC, DevSecOps, secure development, and software quality or test automation.
Ideal Candidate Profile
- Has delivered AI-assisted modernization from legacy application analysis through code transformation, testing, or migration—not only prototypes or standalone AI features.
- Can translate AI-generated analysis into engineering deliverables and connect agents to existing enterprise development tools and pipelines.
- Has experience governing AI outputs in enterprise settings; direct KAF experience and reusable modernization accelerators are preferred.