AI role · Open offer

Développeur IA Générative / Generative AI Engineer

Akkodis

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At a glance

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

Employment: Permanent (CDI), Full-time
Workplace: Hybrid
Location: 6 Rue Paul Valéry, 75116 Paris, France · Hybrid
Compensation: EUR 48k-68k/year
Experience level: Senior
Team: GenAI Engineering
Benefits & perks

About this role

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

Akkodis is hiring a Senior Développeur IA Générative / Generative AI Engineer on the GenAI Engineering team (Hybrid · 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.

Akkodis développe des solutions IA générative sur des environnements clients exigeants (industrie, services, finance).

Le rôle vise à transformer des prototypes GenAI en capacités productives durables.

Ce que vous allez faire

Livrer en production des assistants GenAI avec garde-fous et évaluation 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.
NLP

Tools & stack

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

Azure OpenAITool
Regular use of Azure OpenAI in the LLM & generative AI stack—configuration, debugging, and team conventions.
Vector DBsTool
Embedding storage, hybrid search, and freshness strategies for RAG and semantic retrieval.

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: Décris un assistant GenAI avec garde-fous et évaluation.
Several of these show up in recent shipped work—not only on your CV: Python, LangChain, NLP, Azure OpenAI, and Vector DBs.
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 are comfortable with the hybrid rhythm (Hybrid · Paris, France)—onsite collaboration when it matters, deep work when remote.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.

Apply

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What the employer asked for

Décris un assistant GenAI avec garde-fous et évaluation.

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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