S Senior AI Engineer - Freelance Paris ( Non précisé ) Freelance · Senior il y a 2 sem. ›

Zeroday Cyber Academy; Paris; Hybrid; EUR 120,000 - 180,000; Full time

Job summary

Mirakl recherche un ingénieur IA senior pour concevoir, construire et déployer des systèmes IA en production au cœur de nos produits SaaS. Vous travaillerez à l’interface logiciel, ML et IA générative afin de développer des capacités agentiques et des services destinés aux clients et aux équipes internes.

Le poste est en freelance basé à Paris ou Bordeaux avec 1 jour de télétravail par semaine. Expérience significative requise en ingénierie logicielle et IA opérationnelle, avec un focus sur la

Qualifications

• 5+ années d'expérience en génie logiciel, ML ou IA appliquée.
• Forte maîtrise de Python et des fondamentaux du génie logiciel.
• Expérience en systèmes d'IA en production est un plus.

Responsibilities

• Concevoir, construire et déployer des systèmes IA en production pour les opérations internes et les produits.
• Intégrer les systèmes IA dans les plateformes internes et les outils métiers (CRM, data platform, Jira, etc.).
• Explorer et itérer sur des capacités IA, pilotages et expériences utilisateur basées sur les données.
• Assurer sécurité, traçabilité et fiabilité des pipelines IA et des modèles.
• Travailler avec les équipes produit et ingénierie pour maximiser l'impact métier.

Skills

Python

SQL

AI systems

LLMs

LangChain

Docker

Kubernetes

Education

Aucune exigence éducative spécifique

Tools

OpenAI

Anthropic

Gemini

Mistral

LangGraph

LangChain

LlamaIndex

MCP

AWS

GCP

Job description

About Mirakl

Founded in 2012, member of French Tech Next40, Mirakl provides a SaaS marketplace operating system (enterprise marketplaces, AI-powered multichannel selling, retail media, agentic commerce). 750+ employees in 9 offices (Paris, Barcelona, Bordeaux, Boston, London, Munich, New York, Sydney, Tokyo), including 350+ tech team members mainly based in France. Its ecosystem runs 450+ B2C and B2B marketplaces, with brands like Macy's, Decathlon, Carrefour, Asos and Airbus Helicopters.

About the job

Design, build, and scale production-grade AI systems that power the next generation of intelligent commerce. You will work at the intersection of Software Engineering, Machine Learning, and Generative AI to build AI-native products, agentic systems, and platform capabilities used by Mirakl customers and internal teams.

This is a freelance position based in Paris or Bordeaux, with 1 day of remote work per week.

Why now

Generative AI and AI Agents are fundamentally reshaping commerce software and the way teams work. At Mirakl, AI is becoming a core part of the product strategy, from Catalog Transformer and content generation to AI Agents and Agentic Commerce. We are looking for a Senior AI Engineer to transform the way internal teams work, and to have a significant impact on the agentic side of our SaaS products. You won't be joining a company that's thinking about AI. You'll be joining one that's already building it.

1. Design & build AI systems

• Design, build, and deploy production-grade AI systems for Mirakl internal operations.
• Develop solutions leveraging LLMs, RAG, AI Agents, Multimodal AI and evaluation frameworks.
• Architect complex agentic workflows including tools, memory, retrieval, planning, and guardrails.
• Rapidly prototype new capabilities and evolve them into scalable, reliable AI production systems.

2. Integrate across the stack

• Connect AI systems to internal platforms, business applications, and data sources across the company.
• Enable AI agents to interact with systems such as CRM, data platform, Drive, Jira, support tools, and internal knowledge bases.
• Design robust orchestration layers between models, APIs, tools, retrieval systems, and business workflows.
• Ensure reliability, observability, scalability, and maintainability across the entire AI stack.

3. Iterate for impact

• Partner with end users, business teams, Product Managers, and Engineers to identify high-value opportunities for AI.
• Run pilots and experiments, gather qualitative and quantitative feedback, and measure business impact.
• Analyze usage patterns, failure modes, costs, latency, and performance metrics.
• Continuously improve accuracy, reliability, adoption, and user experience through data-driven iteration.

4. Ensure quality, security & reliability

• Implement evaluation frameworks, guardrails, validation layers, and monitoring systems.
• Design AI systems that are secure, explainable, and production-ready.
• Ensure compliance with data security, governance, and access control requirements.
• Document architectures, capabilities, limitations, KPIs, and operational best practices.

5. Drive adoption & enablement

• Build a scalable ecosystem of AI systems and agents that empower both internal teams and customers.
• Support teams in adopting AI-powered workflows and integrating AI into their daily operations.
• Contribute to AI engineering standards, reusable frameworks, and best practices across the company.
• Act as a champion for AI-driven ways of working and help shape Mirakl's transition toward Agentic Commerce.

Stack and tools

• Languages : Python and SQL
• AI stack : OpenAI, Anthropic, Gemini, Mistral and open-source models
• Agentic & retrieval : LangGraph, LangChain, LlamaIndex, MCP and vector databases
• Infrastructure : AWS or GCP, Docker and Kubernetes

What makes you successful

• Strong engineering mindset: able to design reliable and scalable systems
• Strong AI expertise: able to translate the latest AI capabilities into production products
• Strong product mindset: able to balance technical excellence with business impact
• Focus on measurable outcomes, not technical complexity

You’ll love this job if you have:

• 5+ years of experience in Software Engineering, ML Engineering, Applied AI, or related fields
• Strong Python and software engineering fundamentals

Ce qui te ferait sortir du lot (côté sécurité)

Zeroday : sur un poste comme celui-ci, ce qui fait la différence côté sécurité :

• traiter les garde-fous des agents comment du code : limiter les outils exposés, filtrer les sorties, borner les actions possibles avant de brancher un agent sur un CRM ou un Jira ;
• contrôler le périmètre de données qui alimente le RAG par utilisateur, sinon l'agent restitue à l'un ce que l'autre seul avait le droit de lire ;
• ne rien coller de sensible dans les prompts : une requête envoyée à un modèle hébergé chez un tiers quitte l'entreprise, secrets et données clients compris ;
• garder un jeu d'évaluation de non-régression avant tout changement de modèle ou de prompt : sans lui, une régression passe en production sans se signaler.