Software Modernization Enablement Lead Engineer

Key Responsibilities

• Architect AI-Driven Migration Methodology: Design and execute methodologies and tooling to refactor, rearchitect, and translate legacy codebases into modern, cloud-native architectures using AI-augmented tools.
• Build Agentic AI Workflows: Develop and implement multi-agent AI workflows to automate code analysis, logic extraction, and documentation generation.
• Ensure Code Quality: Establish automated and Human-in-the-Loop verification frameworks so AI-generated code is secure, performant, and compliant.
• Automate Testing: Integrate AI tools to automatically generate, execute, and maintain comprehensive unit and integration test suites throughout code translation.

Qualifications

• Education: Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field.
• Experience: 8+ years in software engineering, including a minimum of 3 years in AI application development and demonstrated experience in enterprise application modernization.
• AI/LLM Integration: Hands-on experience building multi-agent AI workflows for code analysis and logic extraction; composable-skills frameworks for legacy modernization; and agentic orchestration for code generation, documentation, and test synthesis.
• Legacy & Modern Languages: Deep expertise in modern languages (.NET C#, ASP.NET Core, Python, Java, Go) and strong familiarity with legacy enterprise environments (WPF, WCF, ASP, C++, C#, or mainframe architectures).
• Cloud Platforms & Infrastructure: Hands-on experience with Kubernetes, containerization, microservices, hybrid edge-to-cloud topologies, and major cloud providers (AWS, Azure).
• Strong Conceptual Command: Advanced knowledge of any major cloud platform is expected at the expert level.
• CI/CD & DevOps: Advanced knowledge of automated pipelines, Infrastructure as Code (IaC), automated unit and integration test pipelines, and Human-in-the-Loop verification frameworks.
• Platforms & Data: Familiarity with both Windows and Linux environments and database technologies.
• Communication & Collaboration: Excellent communication skills with the ability to evaluate solutions through both short-term and long-term lenses in an iterative development cycle, and a track record of working effectively across diverse, cross-functional teams.