• Evaluate and bring on new AI tools and platforms, assessing fit for the team's workflows, managing setup and configuration, and driving adoption across the product organization. • Lower the barrier to entry for non-engineers to leverage AI tools by packaging environments, simplifying setup, and removing infrastructure friction that blocks adoption. • Solve the IT and security challenges required to deploy AI tools in a healthcare environment, setting up authentication flows, managing access patterns, and ensuring compliance with organizational security standards. • Collaborate across the business—including product, engineering, design, IT, operations, commercial, and leadership teams—to identify workflows that can be accelerated with existing AI capabilities and get those tools running for the team. • Create documentation, guides, and training materials that make it easy for non-technical team members to adopt and get value from new tools. • Troubleshoot and maintain the AI tooling stack, diagnosing issues independently and iterating on configurations based on team feedback.

• Develop and iterate realistic prompts that you would ask a junior role to test the relevance and quality of AI-generated insights. • Systematically evaluate divergence between professional venture judgment and AI outputs across deal evaluation, term sheet structuring, and portfolio management contexts. • Translate how VCs evaluate founders, size markets, assess competitive dynamics, and construct portfolios across stages and sectors into problems that push the limits of AI reasoning. • Build and validate real-world investment memos, market analyses, and founder evaluation frameworks used to evaluate frontier AI systems.

• Develop and iterate realistic prompts that you would ask a junior role to test the relevance and quality of AI-generated insights. • Systematically evaluate divergence between professional advisory judgment and AI outputs across asset allocation, alternatives, financial planning, and private client contexts. • Translate how practitioners build tailored portfolios, select managers, navigate tax and estate considerations, and communicate investment rationale to sophisticated clients into problems that push the limits of AI reasoning. • Build and validate real-world portfolio analyses, financial planning frameworks, and client advisory materials used to evaluate frontier AI systems.

• Weiterbildung zur Kompetenzsteigerung im Bereich künstliche Intelligenz • Strategische Bedeutung und Realisierung von KI in Unternehmen • Integration und Anwendung von KI-Technologien • Projektplanung und -management in MS Project • Erfolgreiche Digitalisierungsprojekte