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

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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