
AI Engineer (Backend focused)
About the role
You'll build the AI systems that power taste evals, tooling, API and RL environments - from agent architectures and data pipelines to the product surfaces where users interact with our platform. The work skews backend (synthetic data, embeddings, crawling, evaluation systems) but you'll also ship front-end tooling and gamified experiences when needed. Early stage, high ownership, lots of building from scratch.
What you'll do
Core focus
Design and build agent systems, evaluation pipelines, and synthetic data generation
Create embedding and retrieval infrastructure that scales to millions of requests
Build crawling and scraping systems for visual data across the web
Set up inference serving and APIs for client-facing products
Develop the tooling and infrastructure that makes everything reliable and fast
Also you
Ship internal tools for data operations and external tools for expert annotators
Build gamified product experiences: taste quizzes, leaderboards, reward flows
What we're looking for
4+ years of experience (flexible for exceptional candidates)
Strong Python and systems design background
Deep experience with AI/LLM systems: agent flows, context engineering, embeddings, index building, RAG
Comfortable with web scraping, data extraction, and large-scale data processing
Experience with cloud infrastructure and CI/CD
What actually matters to us
Startup DNA: You've built at early-stage companies (pre-seed to Series C) and operate well in ambiguity
Real AI building experience: You've shipped agent systems, built with LLMs, and understand the craft - whether through your job, open source, or serious personal projects.
Genuine curiosity about taste: This problem is hard, nuanced and undefined. You find that energizing, not frustrating.
Creative problem-solving: We're not optimizing existing systems. We're inventing infrastructure for something that doesn't exist yet.
Bonus points
Open source contributions
Background at creative companies (Figma, Notion, Canva, Adobe, Runway, etc.) or companies with strong index building/crawling (e.g. Parallel Web Systems, Firecrawl, Brave, Luma, Pika).
Personal projects that show you build things because you're curious
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