Data & AI Engineer – Remote (Latin America)

About the role

We are hiring for a fast‑growing US‑based tech startup that is building a high‑scale data engine to ingest public filings, accelerator databases, and LLM‑parsed content. The role is perfect for engineers who thrive in rapid environments, love building scalable systems for structured and unstructured data, and seek full ownership without micromanagement.

Key responsibilities

• Design and implement distributed web‑scraping systems for dynamic/static sites, public data sources, and Form‑D filings.
• Develop, run, and benchmark LLM pipelines, measuring accuracy, latency, cost, and creating automated regression tests for prompts.
• Architect cloud‑native data pipelines on GCP, ensuring reliability, observability, and cost‑efficiency.
• Build backend services and data access layers, collaborating closely with product and engineering teams.

Required profile

• 4+ years of experience building data pipelines, automated ETL, and backend services.
• Proven expertise in web scraping with tools such as Scrapy, Playwright, or Selenium, including distributed scraping using queues (RabbitMQ, Redis).
• Hands‑on experience with LLM APIs, prompt engineering, and model evaluation.
• Experience deploying containerised pipelines (Docker, Airflow) on GCP or AWS.
• Strong SQL knowledge and data modelling with PostgreSQL, Supabase, or BigQuery.
• Fluent English with strong written communication skills.
• Bonus: familiarity with vector databases or streaming architectures.

Required skills

• Python (FastAPI preferred)
• Google Cloud Platform – Cloud Run, Cloud Functions, BigQuery, Pub/Sub
• Supabase & PostgreSQL
• OpenAI API & LLM pipelines
• Scrapy, Playwright, Selenium
• Docker & Airflow
• RabbitMQ, Redis
• SQL and data modelling

What we offer

• 100% remote work from anywhere in Latin America.
• Opportunity to build cutting‑edge LLM data infrastructure from the ground up.
• A culture based on trust, autonomy, and high technical standards.