Most engineers build products for millions of users they'll never meet. In this role, your users are sitting ten feet away, and they're some of the sharpest investors in tech. Greylock's investment team runs on judgment. But the workflows underlying sourcing, market mapping, and due diligence haven't kept pace. We're building AI systems that give our investors a genuine edge, and we need someone who can own that from the ground up.

You'll own problems end-to-end, talking to the partner who needs a better way to evaluate a market, designing the system, shipping it, and iterating when they use it in a live deal process. No PM. No ticket queue. You decide what to build and how. This role is ideal for someone with ~2–5 years of experience who has shipped AI-powered products and is looking to become a founder eventually.

What you'll actually do:

Build and deploy custom agent-based workflows that automate research, sourcing, and diligence across our portfolio and pipeline.
Design and own production systems that integrate LLMs, retrieval pipelines, and structured data into tools our investors rely on daily
Sit in on deal meetings, hear what's broken, and prototype a fix that week
Make hard product calls on what to automate, what to leave manual, where the model isn't good enough yet, and be right more often than not

What we're looking for:

You've built and shipped AI agents or multi-step LLM workflows in production, not just demos
You're a strong full-stack engineer who happens to be deep in AI, not the other way around
You have sharp product instincts: you talk to users, you scope ruthlessly, and you know when to ship ugly and when to build for durability.
You're energized by ambiguity and fast cycles, not frustrated by them
You've worked at a high-caliber startup or team where you had real ownership

Why is this different:

The users are in the room. Your stakeholders are some of the best investors in tech. Feedback loops are hours, not quarters.

The surface area is enormous. Venture touches every industry and every stage. The AI problems here are broad and hard.

You'll have real leverage and ownership. A single tool you build might reshape how we discover the next generational company.

Location: San Francisco (In-Office)

Applied AI Engineer — Greylock Investment Team