The Fashion Intelligence Company

We’re building the AI-native intelligence layer for fashion — starting with trends → design → tech packs, and expanding toward foundational fashion models that power how the industry creates, searches, and manufactures.

This is a true founding role. You’ll help design the core systems, ship v1 with real customers, and set the technical foundation the company will scale on for years.

If you enjoy crawling the messy internet, building resilient data systems, and turning ML into real product — this role is for you.

What You’ll Own

1. Data Ingestion & Pipelines (Core)

Build and own large-scale crawling systems (web, marketplaces, social, visual data).
Design robust data pipelines (ETL / ELT) that handle:
- Rate limits, retries, partial failures
- Deduplication, schema drift, and noisy inputs
Make pipelines observable, debuggable, and production-safe.

2. AI Systems in Production

Design and operate async + sync ML systems:
- Batch jobs, background workers, real-time inference
Work closely with multimodal data (text, images, metadata).
Think deeply about latency, throughput, cost, and reliability.
Build systems that data scientists and product teams can trust.

3. Distributed Backend Systems

Architect backend services that scale with users, data volume, and model complexity.
Make strong tradeoffs around:
- Consistency vs performance
- Simplicity vs flexibility
Own APIs that power designer-facing workflows and internal intelligence layers.

4. Engineering Foundation & CI/CD

Set up and maintain CI/CD pipelines from early days.
Establish deployment, rollback, monitoring, and alerting practices.
Build systems that make it easy to ship fast without breaking things.

Core Requirements (Non-Negotiable)

Strong backend fundamentals
- Proven experience crawling, scraping, or ingesting large, messy datasets.
- Comfortable with databases, queues, caches, background workers.
Systems thinking
- Solid understanding of distributed systems and real-world failure modes.
- Experience building async and sync systems that interact cleanly.
ML-aware engineer
- You understand how ML systems behave in production.
- You can reason about batch pipelines, inference, experimentation, and feedback loops.
- You don’t treat ML as a black box.
CI/CD competence
- You’ve set up or meaningfully worked with CI/CD systems.
- You care about developer velocity, reliability, and testability.

Optional (Strong Plus)

Exposure to fashion tech, marketplaces, or creative tools.
Hands-on experience with multimodal AI (vision + language).
Prior work with highly unstructured, real-world data.

Super Important (Read This Carefully)

Team player
- Low ego, high ownership.
- Comfortable with strong opinions, respectful disagreement, and full commitment once decisions are made.
- Enjoys building with people, not in isolation.
0 → 1 mindset
- Comfortable with ambiguity and incomplete specs.
- Bias toward shipping, learning, and iterating.
- Can build before the path is obvious.

Equity, Growth & Why This Is Special

Meaningful Equity

You’ll receive real founding equity, not symbolic options.
Ownership reflects impact and responsibility, not just time served.
Early architectural decisions here will compound for years — and equity matches that leverage.
Clean cap table, long-term alignment, no games.

Career Trajectory

Start as a Founding Engineer.
Grow into Tech Lead / Head of Engineering / Chief Architect as we scale.
You’ll shape:
- Engineering culture
- Hiring bar
- System architecture
- How AI actually ships to customers

Titles follow responsibility — not the other way around.

Learning Curve You Can’t Buy Later

You’ll get hands-on exposure to:

Large-scale crawling and data infrastructure
Production ML systems (batch + real-time)
Multimodal AI applied to real workflows
Distributed systems under real constraints
Deep collaboration with designers and domain experts

This is the kind of role that:

Makes you a dangerous future founder, or
Makes you a long-term technical leader with rare depth

Talent Density & Who You’ll Work With

You’ll work closely with some of the sharpest AI and systems talent in the space:

Founders with deep experience building and shipping AI systems at scale.
Advisors and collaborators spanning computer vision, applied ML, and fashion-domain experts.
A small, high-bar team that values clear thinking, first-principles reasoning, and shipping real systems over hype.

This is an environment where:

Technical discussions are deep, not performative.
Good ideas win, regardless of who proposes them.
You’ll be constantly challenged — and will level up fast.

Working Style

Small, sharp team.
High trust, high autonomy.
Minimal process, maximal ownership.
You won’t be handed tickets — you’ll be handed problems.

Who This Is Not For

If you prefer clearly defined specs before starting.
If you want a narrow role without product or system ownership.
If you optimize primarily for short-term comp over long-term leverage.

AI Engineer (Full Stack)