AI Engineer (Full-stack)

AI Engineer (Full-stack)

Location: San Francisco, CA (On-site)

Company Description

Our client is building the infrastructure layer that teaches AI systems taste — enabling models to evaluate subjective quality across creative and aesthetic domains.

Their platform develops agent architectures, evaluation systems, synthetic data pipelines, embeddings infrastructure, and reinforcement learning environments that help foundation models and application-layer AI products better understand subjective judgment.

This is a rare opportunity to join an elite early-stage AI company building foundational infrastructure for one of the hardest unsolved challenges in artificial intelligence: teaching models nuanced human taste.

You’ll join a world-class team with backgrounds across frontier AI, search infrastructure, indexing systems, and large-scale model evaluation.

What You Will Do

• Build and ship AI systems across backend and product surfaces
• Design agent harnesses and self-improvement loops
• Build memory systems for autonomous agents
• Design synthetic data generation pipelines
• Develop large-scale evaluation infrastructure
• Build embedding and retrieval systems at production scale
• Create scalable vector search infrastructure
• Develop web crawling and scraping systems for visual datasets
• Build inference serving systems
• Develop APIs powering client-facing AI products
• Build internal tooling for data operations
• Develop external annotation tooling
• Ship full-stack product experiences when needed
• Build gamified user-facing experiences
• Develop reward and leaderboard systems
• Improve system reliability and performance
• Work directly with leadership on technical architecture
• Build core infrastructure from scratch
• Ship rapidly in a highly ambiguous startup environment
• Help define the technical direction of the company

Ideal Candidate Background

• 4+ years of software engineering experience
• Strong backend or full-stack engineering experience
• Strong Python proficiency
• Strong TypeScript / React proficiency
• Experience building production AI systems
• Experience working with LLM systems
• Strong systems design fundamentals
• Experience building scalable infrastructure
• Strong product engineering instincts
• Comfort with ambiguity
• Strong ownership mindset
• Fast execution velocity
• Ability to operate independently
• Strong technical curiosity
• Excellent problem-solving ability
• Comfort building greenfield systems

Strong Signals

• Built agent systems in production
• Designed evaluation pipelines
• Synthetic data generation experience
• Embeddings / vector DB experience
• Built crawling / indexing infrastructure
• Inference serving experience
• LLM orchestration expertise
• LangChain / PydanticAI / LlamaIndex experience
• Built retrieval systems at scale
• Experience with reinforcement learning environments
• Early-stage startup experience
• Open-source contributions
• Strong side projects
• Creative technology background
• Experience at AI-native startups
• Worked on subjective evaluation systems
• Strong product taste
• Experience at indexing/search companies
• High experimentation velocity
• Strong systems architecture judgment
• Built from zero to production repeatedly

Compensation and Benefits

Base salary: $180,000 – $300,000 Equity: 0.25%–0.75% Visa sponsorship available High ownership environment Direct technical influence Early-stage equity upside Greenfield AI infrastructure challenges Work alongside elite AI engineers Fast-moving engineering culture Deep technical autonomy Opportunity to shape foundational AI infrastructure

Why Join

This is an opportunity to work on one of AI’s most technically difficult frontier problems: teaching machines subjective judgment.

You’ll help build infrastructure that enables AI systems to evaluate quality, aesthetics, and taste across domains — work that sits at the intersection of infrastructure engineering, model evaluation, retrieval systems, and agent architectures.

If you want to build foundational AI systems from scratch, work with elite technical talent, and solve genuinely novel problems, this role offers exceptional technical leverage.

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