AI Engineer

About This Opportunity About Ethos

We’re building AI to make humans irreplaceable. Ethos is the platform that matches human expertise to paid opportunities, from advisory roles to consulting opportunities and full-time positions, backed by a16z, General Catalyst and other top investors.

Small team. Flat hierarchy. High ownership. We build first, experiment rapidly, and automate every process after mastering it once. We lead with taste, clarity, and empathy. We are looking for winners with a heart of gold.

The Role

You will build the products that define how knowledge flows between people and organizations. This means two things:

Client-facing: The research and sourcing platform used by investors, consultants, and enterprises to find and engage experts at scale - search, matching, autonomous agents, report generation.

Internal-facing: The systems that automate how we source, screen, match, and manage experts across every opportunity on the platform. If a human does it more than once, you build the system that replaces the repetition.

You will own full slices of product end-to-end - from problem definition through deployment.

Why Ethos

• Early-stage team where your work directly shapes the product and company trajectory.
• Mission that matters: advancing human opportunity in the age of AI.
• Backed by tier-one investors who believe in what we’re building.
• No bureaucracy. High trust, high autonomy, high impact.

Key Requirements

• You are truly AI-native. You build all day long - switching between Claude Code, Cursor, Codex, and whatever ships next week. You have an open-source repo. You build products for yourself and for your friends on weekends. People describe you as restless and entrepreneurial. You’ve probably tried to start a company already, but it’s not the right time to go permanent on your own - so you want to build something that matters with a team that moves as fast as you do.
• You write clean, production-grade code and ship daily, not quarterly.
• You have deep hands-on experience with LLMs - prompt engineering, RAG, agents, evaluation, fine-tuning. Reinforcement Learning and RL environments is a bonus!
• You build full-stack: backend services, APIs, data pipelines, and enough frontend to ship a complete feature.
• No one hands you a spec. You find the problem, scope the solution, and deliver it.
• You have taste - you care about the details that separate a good product from a forgettable one.