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Mercuryo

AI Solutions Engineer

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Description

You will rapidly build practical automation for internal users, including LLM-powered tools, scripts, integrations, agents, and mini-services. You will connect internal systems through APIs and MCP connectors, understand processes before automating them, deliver usable solutions, and hand them off for support.

Responsibilities

  • Build LLM-powered tools for document processing, data extraction, classification, reporting, and internal chat interfaces
  • Integrate internal systems through APIs and MCP connectors
  • Turn prototypes into tools that non-technical teams can use
  • Hand off deployed solutions to support
  • Understand operational processes before automating them

Requirements

  • Engineering experience with Python or TypeScript, APIs, SQL, Git, and deployment
  • Production experience with LLM prompting, structured output, RAG, tool calling, model-error handling, and quality evaluation
  • Daily use of AI coding agents
  • Ability to define problems, choose a technology stack, and deliver solutions to end users

Benefits

  • 22 days of annual leave plus 6 company days and bank holidays
  • Comprehensive health insurance plans
  • Maternity and paternity leave support
  • Extensive benefits program
  • Flexible work schedule
  • Remote work options
  • Modern offices and co-working spaces across 6 countries
  • Working equipment

Skills

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See also

Solutions Engineering jobs by country — openings, pay and top skills →