Senior AI Engineer - Full-Stack (AI Product Development)

Venture Up • United State
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AI Summary

Build AI systems teaching models subjective quality in creative domains. Backend-heavy role with full-stack execution. Small, exceptional team in San Francisco.

Key Highlights
Build AI core: agents, memory loops, eval pipelines, synthetic data
Design retrieval at scale: embeddings, indexing, crawling, scraping
Own inference stack: APIs, serving, tooling for reliability and speed
Invent, don't optimize: build infrastructure for something that doesn't exist yet
Key Responsibilities
Build AI core components
Design retrieval infrastructure at scale
Ship product surfaces for users and clients
Own and improve inference stack
Technical Skills Required
Python React Cloud Infrastructure CI/CD Crawling Scraping Large-scale Data Processing
Benefits & Perks
$180K-$300K base + 0.25-0.75 equity
Visa sponsorship available (O-1, STEM OPT, H-1B)
In-office role with 4-5 days a week in San Francisco

Job Description


AI Engineer (Full-Stack) - help build the creative layer for AI


Are you an engineer who cares about how products really feel? Have you ever shipped something and thought "yeah, that's not quite right" and then kept tweaking until it was? Do you have strong opinions about subjective quality, and the technical chops to encode them into systems?


A well-funded early-stage AI company is hiring 2-3 AI Engineers to help build something genuinely new - the systems that teach AI models what good looks like in subjective domains like design and creative


They've raised a strong seed round from top-tier investors, they're a small team, and their customers include some of the most recognisable names in AI today. The work is backend-heavy with full-stack execution. So agents, evals, embeddings, crawling, synthetic data, plus the product surfaces where users actually interact.


What you'll do

  • Build the AI core: agent harnesses, memory loops, self-improvement systems, evaluation pipelines, synthetic data generation
  • Design retrieval at scale. Embedding and indexing infrastructure that handles millions of requests, plus the crawling and scraping systems that feed it visual data from across the web
  • Ship the product surface. Internal tools for data ops and expert annotators, external tools for clients, gamified flows like taste quizzes, leaderboards, and reward systems
  • tOwn the inference stack. APIs, serving, the tooling that makes everything reliable and fast under load
  • Invent, don't optimise. They're building infrastructure for something that doesn't exist yet, and they need someone who finds that energising


The Team

Small, exceptional, taste-obsessed. Team members from leading startups and hyper-scale product companies, backed by serious AI talent and on a mission to end AI slop and put more taste into the world.


The role is in-office in San Francisco, 4-5 days a week. They want builders who are bought into the mission and want to be in the room with the rest of the team while it gets figured out. This is a critical role and they're moving fast to fill it.


What they're looking for

  • 4+ years of full-stack or backend engineering, with at least one tour at a sub-50-person startup or hyper-growth company
  • You've shipped real AI systems - agent frameworks, RAG pipelines, embedding infrastructure, fine-tuning workflows. Whether at your job, in open source, or in serious side projects you can point to
  • Strong Python, comfortable with React, cloud infra, and CI/CD
  • Comfortable with crawling, scraping, and large-scale data processing
  • Genuine curiosity about taste, design, and subjective quality
  • You operate well in ambiguity, ship fast, and don't need someone to hand you the spec


What they offer

$180K-$300K base + 0.25-0.75 equity

  • A genuine stake in a company solving one of the most interesting problems in AI
  • Visa sponsorship available for O-1, STEM OPT, and H-1B (if exempt from the $100k fee)
  • The chance to build infrastructure that doesn't exist yet, in a category being defined right now


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