Agentic AI Engineer – Mainframe Modernization
Kyndryl (company site, opens in a new tab)5–8 yrsBengaluruOn-siteDirect career pageEst. 30–45 LPA
Posted 14h ago
Reach people at Kyndryl
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Kyndryl you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
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, refactoring and migration.
- Turn legacy code analysis into business rules, dependency maps, documentation and architecture artifacts that teams can use for implementation.
- Own AI quality and security controls—including evaluation, guardrails and Human-in-the-Loop validation—and integrate reusable workflows into enterprise tools and delivery pipelines.
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 frameworks and orchestration, Python, prompt/context engineering, RAG, vector databases and related knowledge retrieval systems.
- Hands-on mainframe modernization experience covering discovery, reverse engineering and dependency analysis across technologies such as COBOL, PL/I, JCL, CICS, IMS and DB2.
- Experience with enterprise integrations and software delivery practices, including APIs/SDKs, Git, CI/CD, SDLC, DevSecOps, quality validation and AI governance.
Ideal Candidate Profile
- Combines production AI engineering with practical mainframe modernization experience; can connect code understanding to transformation and migration work.
- Has delivered code-aware agents and AI-assisted automation for analysis, documentation, testing or code transformation, with outputs validated for enterprise use.
- Can establish reusable orchestration and AI quality practices, and work across mainframe, architecture, cloud and transformation teams; direct KAF experience is preferred.