Lead LLM Architect for Production AI

Licorne Society

Paris

Sur place

EUR 90 000 - 130 000

Plein temps

Il y a 3 jours
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Résumé du poste

Licorne Society is partnering with a fast-growing AI startup to hire a Lead LLM Engineer. You will own the architecture and quality of AI outputs, building end-to-end pipelines and evaluation frameworks that yield reliable, fast results in real workflows.

You will work on designing production systems, improving retrieval and tool usage, and iterating rapidly from real data. A strong focus on reliability and measurable impact guides every decision.

Qualifications

  • Proven experience shipping real LLM systems in production.
  • Strong understanding of RAG, tools, agents and structured outputs.
  • Ability to design full pipelines, not just prompts.
  • Experience building and using evaluation metrics and datasets.
  • Skilled at debugging retrieval, prompts, and model behavior.
  • Comfort with fast iteration from production data and logs.

Responsabilités

  • Design and evolve LLM/agent architecture.
  • Own output quality across key use cases (emails, document analysis, etc.).
  • Build evaluation systems with datasets and metrics.
  • Drive fast iteration loops from production data.
  • Improve retrieval, reasoning, and tool usage for reliability.
  • Ensure production reliability (latency, failure modes, fallback).
  • Collaborate with product and founders on what to build and why.

Connaissances

LLM systems
Evaluation-driven development
Debugging complex failures
Speed of iteration
System architecture
Reliability focus

Outils

Python (FastAPI)
Postgres
Google Cloud
LangGraph
LangChain
PostHog
Langfuse
Azure OpenAI

Description du poste

Licorne Society is partnering with a fast-growing AI startup to hire a Lead LLM Engineer. You will own the architecture and quality of AI outputs, building end-to-end pipelines and evaluation frameworks that yield reliable, fast results in real workflows.

You will work on designing production systems, improving retrieval and tool usage, and iterating rapidly from real data. A strong focus on reliability and measurable impact guides every decision.

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