Summary: We run a concentrated, thesis-driven fund investing at the convergence of AI, technology, and blockchains. We're wrapper-agnostic with exposure spanning equities, convertible bonds, and tokens. We're hiring an analyst who underwrites like a private equity investor and builds as an engineer.
How we invest:- Like PE, in public markets.Every position is a full ownership case - TAM, moat, unit economics, multi-year growth/margin bridges, FCF-based valuation. Concentrated bets, multi-year horizons.
- We buy mispriced optionality.The best setups hide inside companies the market prices as one thing while they quietly gain exposure to AI and blockchain rails - autonomy, agentic commerce, stablecoin settlement, tokenization. We find that embedded optionality and try to quantify it.
- Agnostic on wrapper, rigorous on instrument.The best expression of a thesis might be equity, a convertible, or a token. You move across the capital structure without losing discipline.
Essential Duties and Responsibilities:Includes the following, other duties may be assigned as needed:
- Own deep fundamental research on single names across tech, internet, semis, payments/fintech, and blockchain-linked companies
- Build the full underwrite: operating models, scenario analysis, and valuation you can defend
- Turn convergence catalysts into explicit model inputs, not narrative
- Build and maintain the team's AI research stack - agents, data pipelines, automated monitoring
- Engage management teams, founders, other fund managers and developers across both ecosystems
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily.
Experience & Qualifications:- 4-8 years across investment banking (M&A) and private equity, growth equity, or fundamental public investing at a top firm
- Owner's mindset: you've built models from unit economics up and defended them
- Genuine conviction at the AI blockchain intersection
- BS/BA in finance, economics, or business; strong quantitative foundation
- Ability to work in office a minimum of 4 days a week
The AI-native edge:- LLMs are infrastructure in your workflow, not a search box
- You've built with frontier-model APIs; agents, tool/MCP integrations, retrieval pipelines, coding-assistant projects
- Working Python and SQL; fluency with on-chain and alternative data
- You know where models fail and verify accordingly
- What you've shipped matters more than any certification
Compensation: - If this position will be performed in whole or in part in New York City, the base salary range is $150,000-$200,000. Individual salaries may vary based on factors including, but not limited to, skills, experience, job-related knowledge, and location. In addition to base salary, this position is eligible for a generous discretionary bonus based on individual and fund performance tied to specific investment objective-related KPIs. The compensation package also includes benefits and other forms of compensation, where applicable.
