Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Роль сочетает разработку AI-продуктов в production, работу с данными и взаимодействие с разными командами: можно выстроить новое направление, но задачи могут быть очень разнообразными.
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Актуальные технологии
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
AI & Data Engineer (AI/data engineering): Building end-to-end AI solutions, data pipelines, clean data layers, and production applications for HR, Sales, Marketing, and Operations with an accent on AI-first development, reliable data, and LLM features. Focus on building RAG systems, agents, assistants, evaluations, monitoring, and production-grade automations.
Location: Czechia, Poland, or Prague; Karlín office
Company
hirify.global provides technology-powered fulfillment and logistics services for ecommerce and DTC brands through a proprietary platform and owned fulfillment centers.
What you will do
Identify AI opportunities across HR, Sales, Marketing, and Operations and turn them into scoped projects.
Build, deploy, secure, monitor, and maintain AI-powered applications and automations used by real people.
Build pipelines from business systems into Snowflake and create clean, tested data layers in dbt.
Develop LLM features including RAG systems, agents, and assistants with evaluations and monitoring.
Drive AI enablement through tools, templates, sessions, and guidance for colleagues.
Experiment with new AI tools and retain effective solutions.
Requirements
Work AI-first with tools such as Claude Code or Cursor as part of daily development.
Experience deploying applications built with AI coding tools to production, including hosting, security, monitoring, and real user adoption.
Experience building at least one data pipeline and data model relied on by others for reporting, an application, or a product.
Strong Python and SQL skills.
Hands-on experience with an analytical warehouse such as Snowflake and an orchestrator such as Airflow.
Ability to explain technical trade-offs clearly to non-technical colleagues.
At least 3 years of hands-on engineering experience in data, software, or AI.
Nice to have
Production experience with dbt.
Experience with Pydantic AI, Langfuse, or similar AI tooling.
TypeScript for simple front ends.
n8n, Zapier, or MCP integrations.
Culture & Benefits
Build a new AI domain from the ground up with visible impact in the first months.
Short path to leadership with few management layers.
Work with real data at scale across a company of 2,500+ people in five countries.
Time to experiment with new AI tools.
Work in a small senior team at the Karlín office.
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