AI role · Open offer

Développeur IA / RAG / Python

BI SOLUTIONS

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At a glance

How you'll work, where, and key listing dates.

Employment: Freelance
Workplace: Remote
Location: 21 Rue de Flandre, 75019 Paris, France · Remote
Compensation: EUR 400-550/day
Experience level: Senior
Team: RAG Platform
Benefits & perks

About this role

What the team is looking for and how this position fits.

BI SOLUTIONS is hiring a Senior Développeur IA / RAG / Python on the RAG Platform team (Remote · Paris, France). This is a hands-on role in LLM & generative AI—not a generic “AI enthusiast” post.

You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

BI SOLUTIONS intervient sur des plateformes RAG en IDF avec exigences de performance et gouvernance des données.

Mission orientée Python + retrieval, avec forte autonomie et ownership production.

Ce que vous allez faire

Livrer en production des pipelines RAG avec contraintes de coût et latence avec évaluation offline, monitoring et plan de rollback.
Travailler avec produit, métier et design pour cadrer les besoins et priorités.
Améliorer qualité des données, observabilité et KPI business liés aux usages IA.
Documenter runbooks, incidents et standards de sécurité pour l'équipe.

Profil recherché

Expérience concrète Python / stack ML-LLM avec features déjà déployées.
Bonne pratique SQL, expérimentation et communication claire aux non-tech.
Capacité à gérer les compromis qualité, coût, latence et sécurité.

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
LangChain
Orchestrating LLM chains, tools, and retrieval with observable steps and failure handling.
SQL

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

Vector DBsTool
Embedding storage, hybrid search, and freshness strategies for RAG and semantic retrieval.
DockerTool
Containerized services and reproducible dev environments for ML and LLM workloads.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

You can show evidence in your application: Montre une architecture RAG avec coût/latence monitorés.
Several of these show up in recent shipped work—not only on your CV: Python, LangChain, SQL, Vector DBs, and Docker.
You have owned LLM features, retrieval, agents, and evaluation in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You communicate clearly in writing, document decisions, and can overlap with the team’s core hours for pairing and incident response.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.

Apply

Candidate accounts only: add your headline and bio on , and optionally a CV link or PDF so recruiters see your full résumé. Then write a short pitch below—applications use your login email.

What the employer asked for

Montre une architecture RAG avec coût/latence monitorés.

Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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Top skills

Python

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