This study examines the conditions of trust under which managers can imagine accepting AI-based agents as individual partners for career development in order to mitigate the risk of leadership failure. Based on eight problem-centred, semi-structured interviews with C-level managers in Germany, this research identifies multidimensional trust requirements essential for successful Human-AI Teaming (HAIT) in this unique executive context. Anchored in a Design Science Research (DSR) framework, the study elaborates the Relevance and Rigor Cycles while projecting implications for future artifact design. Results contribute to the theory of trust in hybrid human-AI networks by expanding the Human-AI-Interaction model by Kaplan et al. (2023). Additionally, the study findings propose a set of preliminary design principles for trustworthy AI agents in executive development contexts.