AI & Data Engineer

We are ShipMonk, and we provide logistics services in order fulfillment. Our main business is in the USA, but our modern platform is built by the Product Development team in Prague. Here at ShipMonk, we process up to 100,000 orders per day in our peak season. Our book of business has more than 1,500 clients, which are small and medium e-shops, mostly based in the US. We offer the ShipMonk platform as the solution for the whole process. It covers everything from stocking the items to shipping the ready packages to all corners of the world! AI-first builder, grounded in solid data. ShipMonk runs ecommerce fulfillment for 1,500+ brands from 12+ fulfillment centers, up to 100,000 orders a day in peak season. The platform is built in Prague. We are starting an AI domain inside our Data team, and we want an engineer who builds AI-first and knows that good AI needs good data. You will look across HR, Sales, Marketing and Operations for places where AI can save time or money. Then you build the solution end to end: the data, the AI logic and the app people use. You will also help colleagues get more out of AI themselves.

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What You'll Do

• Find AI opportunities in business teams and turn them into scoped projects
• Build and ship apps and automations with AI coding tools, and run them in production
• Build pipelines from business systems into Snowflake and model clean, tested data layers in dbt
• Build LLM features on that data: RAG, agents, assistants, with evals and monitoring
• Drive AI enablement: share tools and templates, run sessions, help colleagues work AI-first
• Experiment with new AI tools and keep what works

What You’ll Bring

• You work AI-first. Tools such as Claude Code or Cursor are part of how you build every day.
• You have deployed apps built this way to production: hosted, secured, monitored and used by real people, not only demos.
• You have built at least one data pipeline and data model that other people relied on, for reporting, an app or a product.
• Strong Python and SQL
• Hands-on experience with an analytical warehouse (Snowflake or similar) and an orchestrator (Airflow or similar)
• You explain technical trade-offs clearly to non-technical colleagues
• 3+ years of hands-on engineering in data, software or AI

Nice To Have

• dbt in production
• Pydantic AI, Langfuse or similar AI tooling
• TypeScript for simple front ends
• n8n, Zapier or MCP integrations

Why Join?

• Build a new AI domain from the ground up, with visible impact in the first months
• Short path to leadership and few management layers
• Real data at scale: 2,500+ people in five countries
• Time to experiment with new AI tools
• Karlín office, small senior team

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