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Mainframe Modernization Lead - AI-Powered Reverse Engineering

CloudiousAustin, TX🇺🇸United StatesPosted 10 Sept 2026

Why This Role Stands Out

Lead groundbreaking mainframe modernization initiatives using AI-powered reverse engineering, offering significant career growth and skill development in the dynamic finance sector. This hybrid role is perfect for innovative mid-senior professionals who thrive on complex challenges and enjoy collaborating within a forward-thinking team. Apply to make a substantial impact at a reputable company.

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Austin, TX, United States
Posted
6 days ago
SAFeAWSAzureCOBOLGenerative AIGoogle CloudJavaPMPReconciliationRisk ManagementStakeholder Management

Job Description

Position Title

Mainframe Modernization Lead

Domain

Banking / Finance

Location

Austin, TX

No of Positions

2

Hire Type

FTE and C2H

Skills

Finance, Payment and Capital Market Domain Specialist

Salary

Job Description

JOB DESCRIPTION

Mainframe Modernization Lead

AI-Powered Reverse Engineering

Experience
15+ years

Location
Austin, Texas

Role Type
Contractor / Full-time

Role Summary

Lead AI-assisted reverse engineering and modernization of complex Mainframe applications. The role is responsible for recovering business logic, application dependencies, data flows, and functional behavior from legacy systems and converting the findings into validated artifacts that enable modernization planning and delivery.

Key Responsibilities
  • Lead discovery and reverse engineering across COBOL, JCL, CICS, DB2, IMS, VSAM, MQ, copybooks, batch workloads, interfaces, and supporting documentation.
  • Use AI and specialized analysis tools for code understanding, business rule extraction, call graph generation, dependency mapping, data lineage, documentation, and test scenario discovery.
  • Validate AI-generated outputs with Mainframe SMEs, business SMEs, architects, and quality teams, ensuring traceability to source evidence.
  • Create application inventories, business rule catalogs, functional and technical specifications, process flows, interface mappings, data mappings, and modernization backlogs.
  • Identify candidate APIs, services, events, reusable components, and modernization options such as rehost, replatform, refactor, rewrite, replace, or retire.
  • Support estimation, migration sequencing, parallel testing, reconciliation, cutover planning, and functional equivalence validation.
  • Lead cross-functional teams and communicate progress, risks, dependencies, decisions, and outcomes to program leadership and client stakeholders.
Required Experience and Skills
  • 15+ years of Mainframe engineering, architecture, application assessment, or modernization experience.
  • Deep knowledge of COBOL, JCL, CICS, DB2, IMS, VSAM, MQ, batch processing, schedulers, and Mainframe integration patterns.
  • Leadership experience in at least two large-scale Mainframe modernization programs, preferably involving COBOL-to-Java or cloud transformation.
  • Hands-on understanding of Generative AI, code intelligence, static analysis, automated documentation, RAG, vector search, knowledge graphs, or agentic workflows.
  • Expertise in business rule extraction, call graph and impact analysis, functional decomposition, data lineage, interface analysis, and service identification.
  • Strong stakeholder management, workshop facilitation, technical writing, risk management, and executive communication skills.
Preferred Qualifications
  • Experience with Azure, AWS, or Google Cloud modernization programs.
  • Experience in banking, brokerage, payments, insurance, or another regulated industry.
  • Exposure to dual-run, reconciliation, regression testing, and production cutover for critical systems.
  • Cloud, TOGAF, PMP, SAFe, or comparable certification.
Key Deliverables

Area

Expected Outputs

Reverse Engineering

Application inventory, call graphs, dependency maps, business rules, data lineage, process flows

Modernization Readiness

Functional and technical specifications, service/API candidates, target-state inputs, migration backlog

Validation

Traceability matrix, SME review evidence, comparison scenarios, regression and reconciliation scope

Knowledge Transfer

Governed knowledge repository, runbooks, technical handover, and training materials

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