The accelerating addition of artificial intelligence (AI) into engineering practice and education demands more than technical proficiency - it requires a literate, critical mindset capable of navigating algorithmic systems, ethical dilemmas, and socio-technical transformations. This paper presents a conceptual framework for Critical AI Literacy (CAL) tailored to engineering education. Based on contemporary research in AI literacy, data ethics, and engineering education, the framework delineates four interrelated dimensions: Awareness, Technical Fluency, Ethical Agency, and Critical Reflection, and includes them in educational pathways for addition into undergraduate engineering programs. By shifting from an instrumental view of AI competence (i.e., 'how to use' AI) to a reflective, agency-centered orientation (i.e., 'how to understand and question' AI), the proposed CAL framework offers educators and program designers a structured lens for developing engineers who are not only technically capable but also ethically and critically aware. Implications for curriculum design, faculty development, and future research are discussed. As a conceptual contribution, this paper is intended as a foundational proposition for future empirical validation and development.
