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Senior AI Product Engineer

Smeetz

Senior 🇬🇧 English
Claude Code Langfuse Observability

Description du poste

About the role

Smeetz is an AI‑powered unified commerce platform serving the European leisure and entertainment sector. As a Senior AI Product Engineer you will own the two AI surfaces – the Smeetz MCP server and the AI chatbot – from concept to production, working directly with venue operators and making product decisions without an intermediary product manager.

Key responsibilities

  • Own the end‑to‑end development, operation and continuous improvement of the MCP server and AI chatbot.
  • Conduct discovery independently: talk to venue operators, analyse usage traces, define specifications, ship features and measure impact.
  • Maintain reliability, latency and error‑rate targets; use full observability data to drive performance improvements.
  • Build and maintain an evaluation layer to make prompt and model changes measurable before release.
  • Document the AI surfaces thoroughly so future engineers can understand and extend them without additional guidance.
  • Contribute to the shared Claude Code skill library and raise the bar for AI‑native delivery across the engineering team.

Required profile

  • Minimum 5 years of production code experience, including ownership of at least one system with on‑call responsibilities.
  • At least 2 years building LLM‑based features that reached real users (tool calling, structured outputs, evaluation, cost/latency control, production‑grade failure handling).
  • Proven expertise in an AI‑native software development lifecycle, using Claude Code or an equivalent agentic environment daily.
  • Experience designing APIs or tool surfaces for AI agents, focusing on naming, granularity and recoverable error messages.
  • Demonstrated ability to run discovery, write specs and define success metrics independently.
  • Fluent English communication skills.

Required skills

  • LLM development and deployment.
  • Claude Code (or equivalent agentic programming environment).
  • Langfuse or similar LLM observability tools.
  • API design for AI agents.
  • Production‑grade monitoring, evaluation and performance optimisation.

Questions fréquentes

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