Founding Data & AI Engineer, Creative Engine

Sierra Studio

4d•Remote

About The Position

Our hiring partner is looking for its founding engineer on the Creative Engine, and they're hiring data-first, not app-first. This is a data product at its core, and you'll own the foundation: the pipelines that pull and structure performance data across hundreds of accounts, the LLM workflows that analyze every video they run, and the search layer that turns all of it into answers strategists can query. You'll own features end to end, including the UI, but you don't need to be a frontend specialist. The heart of this role is the data and intelligence layer — you'll lean on Claude Code and agentic tooling to ship the dashboards and interfaces on top. Get the foundation right and the product follows, so they want someone who's genuinely LLM-fluent and savvy with AI-native development, not just someone who's heard of it.

Requirements

5+ years building production, data-heavy applications with Python/Django and PostgreSQL (senior / lead level, autonomous, low-process).
Strong SQL well beyond basic ORM queries (aggregations, joins, window functions) and comfort designing schemas and data models straight from use cases.
Experience designing and debugging async data pipelines (Celery + Redis or equivalent).
Genuinely LLM-fluent: hands-on with LLM APIs in production, prompt engineering, structured output, and cost management.
Fluent with agentic coding tools (Claude Code, Cowork) and excited to use them to move fast, including building full-stack on top of your own data work.
Experience integrating messy third-party APIs (rate limits, auth flows, inconsistent data).
Comfortable owning frontend (Django templates + HTMX + Tailwind) with AI assistance — you ship the whole feature, you just don't need to be a frontend expert.
Strong written communication and high ownership on a small, async team.

Nice To Haves

An AI engineer at heart — you've built agent harnesses, RAG, or LLM eval pipelines (even side projects count).
Background in or curiosity about ML fundamentals, like knowing when a simple scoring function beats a complex model.
Experience with video or audio processing pipelines.
Domain experience in ad tech, creator economy, performance marketing, or marketplace platforms.
Have worked with a US-based team before — async, English-fluent, knows the drill.

Responsibilities

Design the data foundation: pipelines that pull, store, and structure performance, sales, and engagement data across hundreds of client accounts (performance creative, TikTok Shop, TikTok LIVE, and Meta), handling the messiness of real platform APIs.
Build the LLM analysis layer, using Gemini to watch and tag every video and Claude for generation, with structured output at scale and sane cost controls.
Build search and discovery with semantic search via pgvector, so a strategist can ask "what are the top hooks for beauty this week?" and get a real answer, not a keyword dump.
Build the "brain": connect viral organic references, top-performing ads, content tags, and creator history into queryable creative intelligence, accessible through the web app, Slack, and Cowork.
Develop creator-performance matching, linking creator history, content tags, and ad metrics to sharpen casting decisions.
Own the full stack on top of your data work: dashboards, tag browsers, enrichment queues, and export tools in Django + HTMX + Tailwind, moving fast with Claude Code (no dedicated frontend hire required).
Integrate external APIs (TikTok, Meta, Motion, Cruva) and internal async pipelines (Celery + Redis).