AI Engineer - Unusual Ventures

Lever, Inc.; San Francisco (CA); On-site; USD 140,000 - 200,000; Full time

Job summary

Unusual Ventures is hiring our first AI Engineer to build internal systems that help our small team operate with scalable leverage across investing, talent, platform, founder services, finance and operations.

You'll own the stack, set technical standards, and decide what to build, working closely with partners and portfolio companies to scope AI features and stand up workflows. This builder role rewards hands-on problem solving over integration of fresh APIs.

Qualifications

• 3–6 years of software engineering experience, with 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 trustSelf-directed: comfortable setting priorities with light direction

Responsibilities

• Build talent intelligence pipelines to find, enrich, and rank engineering and GTM talent for our portfolio — working closely with our Talent Partner to turn our recruiting judgement into repeatable systems.
• Develop sourcing and research tools surfacing 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.
• Create diligence workflows to speed up market maps, competitive analysis, customer-call synthesis, and memo drafting.
• Make firm knowledge searchable and usable from thousands of founder and customer conversations, past memos, playbooks.
• Develop operations automation for portfolio reporting, LP updates, and back-office processes with CFO/O and VP Finance.
• Build portfolio support tools and reusable AI playbooks for our founder services team to deploy across portfolio companies.

Skills

Python

TypeScript

LLM APIs

Data pipelines

APIs

Frontend development

User research

Education

BS/MS in Computer Science/Engineering/Math or related field

Job description

About Unusual

Unusual Ventures is an early‑stage venture firm that partners with exceptional enterprise software founders from pre‑seed through Series B. We work hands‑on with founders on go‑to‑market, customer discovery, and recruiting, with one goal: helping companies find product‑market fit.

We want AI built into how we source, evaluate, support, and run the firm — not bolted on.

About the Role

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 judgement 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 trustSelf‑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.