Generative AI and AI agents are changing software development practices and the competencies expected of software engineers. In addition to developing software artifacts, engineers increasingly need to work with AI systems, evaluate AI-generated outputs, and maintain responsibility for technical decisions made with AI support. This study reviews recent developments in AI-assisted software engineering, as well as competency-based education, computing curriculum guidelines, and responsible AI principles, to examine their implications for Software Engineering education. From this analysis, we propose a Software Engineer 2.0 Education and Assessment Framework. The framework retains core Computer Science and Software Engineering foundations while extending graduate competencies toward three areas: Validation, Orchestration, and Accountability. These competencies are developed progressively, from independent mastery of foundational knowledge to AI-assisted development and validation, and finally to the orchestration of AI agents in software projects. The assessment approach follows the same progression by examining students' independent technical competence, their ability to evaluate AI-generated artifacts, and their ability to explain and justify their use of AI. The framework is intended as a reference for universities seeking to adapt Software Engineering curricula to AI-augmented software development

Software Engineer 2.0, Software Engineering Education, Competency-Based Education, Generative AI, Agentic AI; AI-Driven SDLC.