We're hiring our first AI Engineer to build the internal systems that can help our small team operate with scalable leverage. You'll work across the firm - investing, talent, platform, founder services, finance and operations - finding the highest-leverage problems, then designing, building, and shipping tools people use every day.
You'll be our first engineer. That means real ownership and a lot of trust, and it also means you'll set the technical standards, choose the stack, and decide what's worth building.
This is a builder role. We care more about solving the underlying problem well than wiring together the newest APIs. You'll have real ownership, direct access to partners and operators, and a short path from idea to production.
From time to time you'll also work directly with portfolio companies: helping founders scope an AI feature, pressure-test their technical approach, or stand up an internal workflow.
What You'll Build (Example projects for your first year):- Talent intelligence. Agents and pipelines that find, enrich, and rank engineering and GTM talent for our portfolio - working closely with our Talent Partner to turn our recruiting judgment into repeatable systems.
- Sourcing and research. Tools that surface promising companies and founders early, and context-aware research assistants that draw on our CRM, notes, meeting history, and market data to prep partners before a first meeting.
- Diligence support. Workflows that speed up market maps, competitive analysis, customer-call synthesis, and memo drafting - without losing rigor.
- Firm knowledge. Making what the firm already knows (thousands of founder and customer conversations, past memos, playbooks) searchable and useful.
- Operations automation. Removing manual work from portfolio reporting, LP updates, and back-office processes, in partnership with the CFO/O and VP Finance.
- Portfolio support. Reusable AI playbooks and tools that our founder services team can deploy across portfolio companies.
What We're Looking For (Required)- 3-6 years of software engineering experience, with at least 1-2 years shipping LLM-powered products or internal tools to production
- BS or MS in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience
- Strong Python (TypeScript a plus); comfortable across the stack, from data pipelines and APIs to a simple, usable front end
- Hands-on experience with LLM APIs, retrieval, agents/tool use, and evaluation - and a clear view on when each is the wrong tool
- Product taste: you talk to users, find the real problem, ship something small, and iterate
- Experience working with messy real-world data (CRMs, email, calendars, third-party data providers)
- Clear communicator who can explain tradeoffs to non-technical partners and earn their trust
- Self-directed: comfortable setting priorities with light direction
Nice to have- Experience building internal tools or intelligence products at a VC firm, investment firm, or data-heavy operations team
- Early-stage startup experience, or time as a founder
- Familiarity with venture or enterprise software GTM
- Experience with recruiting or people data
- Public work - open-source projects, side projects, writing - that shows how you think and build
How We Work- Small team, high leverage. Your tools will be used daily by the whole firm, and you'll see the impact directly.
- Build, don't just integrate. Buy off the shelf when it's the right call; build when the problem calls for it.
- In person. We work together in the Bay Area office. Being close to the people using your tools is part of the job.
- Founders first. Everything we build should ultimately make us more useful to the founders we back.
How to ApplySend your resume or LinkedIn, plus a short note about something you've built with AI that people actually use - what the problem was, what you shipped, and what you'd do differently. Links to code or demos are welcome.
