Join EY as a Senior Mainframe Modernization Specialist and be at the forefront of transforming legacy systems. This role is key to our AI-Driven Modernization practice, focusing on evolving mainframe environments into agile, cloud-ready platforms. You'll leverage a strong foundation in mainframe technologies, AI tools, and cloud solutions, collaborating closely with diverse teams to achieve scalable modernization outcomes. Your expertise will be crucial in analyzing legacy applications, employing AI/ML for code analysis and refactoring, and migrating mainframe workloads to modern, distributed, and cloud-native infrastructures.

Your primary responsibilities will involve in-depth analysis and understanding of mainframe systems (COBOL, JCL, VSAM, DB2, CICS, IMS) to pinpoint modernization opportunities and interdependencies. You'll document existing architectures, data flows, and integration points, while performing impact assessments for transitions. A significant part of this role includes applying AI tools and custom AI workflows for automated code analysis, refactoring, and reducing technical debt. You will develop and fine-tune AI assistants to accelerate system conversion, utilizing prompt and context engineering for LLM-driven modernization. Executing modernization tasks such as rehosting, refactoring, or rebuilding mainframe workloads, and contributing to the design of target-state cloud-native architectures are also key. You'll ensure code quality, develop API integrations and microservices, and support the migration of workloads to cloud platforms like AWS, Azure, or Google Cloud, integrating with containerized solutions and CI/CD pipelines. Maintaining technical documentation and providing regular progress updates are also expected.

We are seeking candidates with a Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. A minimum of 5 to 9 years of hands-on experience with legacy mainframe systems, including COBOL, JCL, Assembler, CICS, DB2, IMS, and VSAM, is essential. Proven experience in data migration, integration, ETL processes, and familiarity with at least one major cloud platform (AWS, Azure, or Google Cloud) is required. Proficiency in programming/scripting languages such as Python and/or Java, along with working knowledge of APIs, microservices architecture, and containerization tools like Docker and Kubernetes, is crucial. Direct experience with AI tools, LLM API calls, prompt engineering, and context engineering for automating code analysis and modernization workflows is highly valued. Experience with specific mainframe modernization tools is considered a plus. Strong analytical, problem-solving, and communication skills are also necessary to effectively collaborate with cross-functional teams and translate complex technical concepts.