Software Modernization Software Engineer (LLM-Focused)Role OverviewWe are building an engineering team that can harness the transformative power of generative AI to modernize legacy software applications. In this role, you will leverage cutting-edge AI technology to analyze, refactor, and transform complex codebases into modern, cloud-based solutions. You will be a key contributor in shaping our modernization strategy and driving innovation within our organization.
Desired Qualifications- Hands-on experience using LLMs through APIs (e.g., Claude, Gemini)
- Familiarity with different LLM architectures and their strengths/weaknesses
- Understanding of prompt engineering techniques to optimize LLM output
- Hands-on technical experience with cloud computing, including designing, deploying, and managing cloud-based solutions
What we are looking for in a strong candidate- Cloud certifications in the area of architecture, data engineering, and/or machine learning
- Background working with government technology projects and programs
- Demonstrated ability to connect with stakeholders
- Bachelor's degree or equivalent experience required
Key Responsibilities- Legacy Code Analysis and Understanding:
- Leverage generative AI tools to analyze and understand complex legacy mainframe codebases (COBOL, PL/I, etc.).
- Identify patterns, dependencies, and potential areas for optimization.
- Generative AI-Powered Modernization:
- Utilize AI to assist in refactoring, translating, or re-architecting mainframe applications into modern languages and architectures (Java, Python, microservices, etc.).
- Implement AI-driven code generation to accelerate modernization efforts while ensuring code quality and maintainability.
- Data Migration and Integration:
- Design and implement strategies for migrating data from legacy mainframe systems to modern databases or cloud platforms.
- Leverage AI to automate data transformation and ensure data integrity.
- Testing and Validation:
- Develop and execute comprehensive testing plans to ensure modernized applications meet functional and performance requirements.
- Utilize AI for automated test case generation and test execution.
- Collaboration and Innovation:
- Work closely with mainframe experts, architects, and other developers to understand modernization goals and constraints.
- Stay abreast of the latest advancements in generative AI and apply them to improve modernization processes.
