Private Equity & Growth Equity - AI Residency (Part-time) | Frontier AI Research (US)

About Us Mentis AI works at the intersection of institutional investment expertise and frontier AI systems. Our team combines deep asset management experience (Lazard, Partners Group) with machine learning and applied AI research. Operating across London and San Francisco, we collaborate with leading AI labs to improve how models reason, generalize, and make decisions in high-stakes financial contexts.

The Opportunity This residency is designed for senior research analysts and portfolio managers who want exposure and a meaningful experience towards the direction of AI in your domain and earn early, practical exposure at using advanced AI system.

You will:

• Prompt: Develop and iterate realistic prompts that you would ask a junior role to test the relevance and quality of AI-generated insights.

• Compare human vs. machine judgment: Systematically evaluate divergence between professional investment reasoning and AI outputs.

• Design frameworks: Translate how investors navigate uncertainty, stress assumptions, and structure transactions into problems that push the limits of AI reasoning.

• Construct expert benchmarks: Build and validate real-world financial models, returns analyses, and investment cases used to evaluate frontier AI systems.

Why This Experience Is Valuable

• Hands-on exposure to how rapidly AI is reshaping deal workflows, from screening and diligence to portfolio monitoring and exit preparation.

• You will be among the first investment professionals to work directly on how frontier AI models reason about private markets.

Who You Are

• 3 to 7 years of experience in PE or Growth Equity at a renowned large-cap or upper-middle market fund in Europe or the US

• Associate, VP, or Principal level; industry agnostic.

• Strong modeling and valuation skills with experience across the full deal lifecycle.

• Genuine intellectual curiosity about application of AI in finance

Residency Structure

• Commitment: 15+ hours/week, flexible scheduling

• Location: Remote globally

• Compensation: Hourly rate depending on experience

• Start date: Immediate / Rolling