Full-Stack AI Engineer
Lima, Peru, PeruAll locationsLima, Peru, PeruCape Town, South Africa, South AfricaAsuncion, Parugauy, ParaguayGuayaquil, Ecuador, EcuadorKharkiv, Kharkiv, UkraineMonterrey, Mexico, MexicoCairo, Egypt, EgyptJohannesburg, South Africa, South AfricaBogotá, Columbia, ColombiaMedellín, Columbia, ColombiaSantiago, Santiago, ChileMontevideo, Montevideo, UruguaySanto Domingo, Dominican Republic, Dominican RepublicManagua, Nicaragua, NicaraguaKingston, Surrey, JamaicaBuenos Aires, Argentina, ArgentinaPanama City, Panama, PanamaTegucigalpa, Honduras, HondurasWarsaw, Warsaw, Poland Remote
$30,000–$36,000 a yearJobFig found this opening at its original source and checks that it remains available.
About the role
We are seeking a senior Full-Stack AI Engineer to join our platform team and own the end-to-end build of a data ingestion and intelligence layer for enterprise customers in the media vertical. This is a high-impact, high-ownership role at the intersection of AI, data engineering, and product. You will architect and ship pipelines that transform unstructured creative assets and ad performance data into a semantic, vector-based layer and expose it through AI agents and a polished React frontend. We move fast, ship to production, and hold a high bar for craft and reliability.
What you'll bring
- Strong TypeScript — you use types as a design tool, not a formality
- Production experience with serverless or edge runtimes (Cloudflare Workers, Vercel, Lambda, Deno Deploy, or equivalent)
- Demonstrated experience building durable, idempotent ingestion pipelines with queuing, retry logic, backpressure handling, deduplication, and schema evolution
- Practical, production-level understanding of embeddings, chunking strategies, and retrieval quality tuning
- At least one agent-style system shipped to production: tool use, stateful multi-step workflows — framework matters less than the experience
- React fluency with modern patterns and component architecture
- Comfort operating across two cloud environments
- able to reason clearly about when to use edge compute vs. managed data/AI services, and how to bridge them
- Applications without this experience will not be considered.
- Must have prior remote work experience, be fluent with remote collaboration tools and platforms (such as Slack, Zoom, Google Workspace, Linear, or similar), and have ideally worked with US or UK-based companies.
- Experience building or operating RAG systems in production
- Familiarity with current embedding models and the tradeoffs across dimension, quality, and cost