AI Engineer

• Automatiser les workflows métier entre nos différents outils
• Traiter les données en entrée de nos process
• Mettre à disposition des skills IA partagés, réutilisables par toutes les BU
• Faire grandir une communauté interne autour de l'utilisation de l'IA
• Concevoir et déployer des workflows automatisés sur n8n ou équivalent, connectant nos outils métier
• Identifier les tâches répétitives à fort impact et les transformer en flux autonomes
• Concevoir et maintenir des pipelines d'extraction et de structuration de documents métier
• Travailler en lien avec les data engineers pour intégrer ces outputs dans les pipelines de données du groupe
• Construire une bibliothèque de skills et d'agents IA réutilisables
• Animer une communauté interne de pratiques autour de l'IA

AI Ops Engineer – F/H

• Defining the long-term vision and technical strategy for our GenAI Platform
• Building the infrastructure that powers image generation, video generation, model serving, orchestration, evaluation and agentic workflows
• Partnering with Research to rapidly bring new models into production
• Driving platform reliability, scalability and cost efficiency across billions of inference requests
• Leading and growing a multidisciplinary team of ML Engineers, Software Engineers and Researchers
• Creating an environment where ambitious technical ideas can move from research to production in days rather than months
• Working closely with Product, Engineering and Executive leadership to ensure platform investments directly accelerate product innovation

Head of GenAI Platform

• Piloter la stratégie IA du projet : expérimenter, tester et industrialiser l'usage des LLMs
• Garantir la qualité logicielle : concevoir des architectures robustes et itérer rapidement
• Implémenter des agents IA pour développer des fonctionnalités innovantes et améliorer les pratiques de développement
• Travailler de manière itérative, livrer régulièrement de la valeur aux utilisateurs et mettre en place une boucle de feedback courte

Consultant, AI Software Engineer, SDLC

• Design and develop AI solutions in Python.
• Implement Retrieval-Augmented Generation (RAG) pipelines to improve model relevance.
• Leverage the AWS cloud, particularly AI/LLM services (e.g., Bedrock).
• Integrate AI tools and orchestration platforms (N8N, OpenAI, Claude, …).
• Conduct experiments and drive continuous improvement through prompt engineering and model fine-tuning.
• Monitor AI technology trends and propose ideas/concepts to enhance our products.
• Collaborate with product, data, and engineering teams to industrialize reliable, scalable AI solutions.

Experienced AI Developer

• AI is central to 360Learning's strategy: our AI Squad ships agentic features that help users discover, create, and administrate content.
• Build a global view of our codebase and architecture (Pydantic AI, FastAPI, Azure OpenAI, ElasticSearch)
• Contribute meaningfully to an existing feature, hands-on
• Coach our team of AI Engineers (2 today, growing)
• Own end-to-end delivery of a new AI feature, from technical design through production launch
• Optimize for real-world constraints: reduce per-request cost, improve latency, and scale to handle usage spikes
• Set the technical direction for AI features alongside the PM's product vision
• Push technical innovation within the squad and across R&D (e.g. hackathons, transversal initiatives) while keeping roughly 80% hands-on and ~20% on coaching and management

Lead AI Engineer

• Design and development of AI solutions in Python
• Implementation of RAG (Retrieval Augmented Generation) pipelines to improve model relevance
• Utilization of the AWS cloud, with a focus on AI/LLM services (e.g., Bedrock)
• Integration of AI tools and orchestration platforms (N8N, OpenAI, Claude, ...)
• Experimentation and continuous improvement through prompt engineering and model fine-tuning
• Keeping up-to-date with AI innovations and proposing ideas/concepts to enrich our products
• Collaboration with product, data and development teams to industrialize reliable, scalable AI solutions

Senior AI Developer

• The AI Engineer designs, deploys and industrializes generative AI, machine learning and automation solutions to support various business functions (education/pedagogy, learner relations, internal teams)
• Transform concrete business needs into reliable, measurable and controlled AI products (costs, latency, compliance), from scoping through production
• Define and scope requirements expressed by different teams, estimate ROI and make build-vs-buy and implementation trade-offs
• Design and industrialize generative AI and ML solutions: RAG (retrieval-augmented generation), educational and administrative chatbots, agents, automations
• Document, harden and evolve solutions (CI/CD, Dev/Staging/Prod environments)

• Design and implement AI solutions using Large Language Models (LLMs), retrieval-augmented generation (RAG), and agentic frameworks to address complex business challenges
• Build and maintain information retrieval pipelines, including hybrid search (sparse + dense), vector databases, and multi-stage re-ranking systems
• Develop and fine-tune LLMs and vision-language models (VLMs) for domain-specific tasks such as product categorization, attribute extraction, and semantic search
• Build and orchestrate agentic AI systems that interact with internal tools and external data sources
• Write production-ready code and deploy AI systems at scale in live environments
• Define and track evaluation metrics aligned with product and business goals; run controlled experiments (A/B tests, benchmarks) and clearly communicate results
• Collaborate with software engineers, product managers, and business stakeholders to frame problems from both scientific and business perspectives
• Investigate and resolve production issues; ensure reliability, observability, and performance of AI systems
• Keep up to date with the latest AI trends (Generative AI, agentic systems, scalable ML, etc.)

• Design and develop AI solutions in Python.
• Implement RAG (Retrieval-Augmented Generation) pipelines to improve model relevance.
• Leverage AWS cloud services, in particular AI/LLM services (e.g., Bedrock).
• Integrate AI tools and orchestration (N8N, OpenAI, Claude, etc.).
• Experiment and continuously improve via prompt engineering and model fine-tuning.
• Monitor AI technology trends and propose ideas/concepts to enhance our products.
• Collaborate with product, data, and development teams to productionize reliable, scalable AI solutions.

• Conception et développement de solutions IA en Python.
• Mise en place de pipelines RAG (Retrieval Augmented Generation).
• Exploitation du cloud AWS et en particulier des services IA/LLM (ex. Bedrock).
• Intégration d’outils IA et d’orchestration (N8N, OpenAI, Claude, …).
• Collaboration avec les équipes produit, data et dev.
• Veille technologique sur les innovations IA et proposition d’idées/concepts.

Développeur confirmé, IA

• Map current-state workflows end-to-end to diagnose root causes of operational friction, including handoff failures, governance gaps, and tooling mismatches.
• Redesign target-state operations for leaner workflows, clearer decision rights, and effective human-agent collaboration to accelerate throughput using AI.
• Design comprehensive operating models, including organizational structure, roles, governance, cross-functional interaction models, and value realization.
• Establish performance baselines and build measurement frameworks that track improvement continuously throughout the engagement.
• Identify value gaps in stalled implementations, diagnosing where technology deployment has outpaced business adoption to restore the path to ROI.
• Build working, AI-powered prototypes directly utilizing LLM APIs, platform-native features, and low-code/no-code environments to create functional solutions.
• Utilize working demos and prototypes as the primary tool for stakeholder alignment directly within the client's actual processes.
• Evaluate where AI practically enhances a workflow versus where it serves as a distraction, advising clients with realistic, grounded expectations.
• Support the rollout of new tools and workflows, ensuring adoption is rooted in process design and change management.
• Design enablement materials that ensure new technology implementations effectively connect to and support the intended operating model.
• Support complex engagement scoping and conduct diagnostic assessments for value capture, implementation readiness, and adoption strategy.
• Contribute reusable frameworks and tools that continuously improve practice qualification and scoping.

Forward Deployed Engineer – AI, Business Transformation

• Map creative workflows end-to-end, including briefing, concepting, production, review, localization, activation, and measurement.
• Identify operational bottlenecks, inefficiencies, and opportunities for automation.
• Diagnose root causes of workflow friction, including approval delays, handoff failures, tooling gaps, and governance challenges.
• Design future-state workflows that effectively balance AI automation and human oversight.
• Configure and implement creative AI platforms and tools against real production requirements.
• Integrate AI-powered workflows into existing ecosystems, including DAMs, CMS platforms, marketing technology stacks, and project management systems.
• Build prompt architectures, agent workflows, automation layers, and quality control mechanisms that can operate reliably at production scale.
• Develop working proofs of concept and production-ready solutions that demonstrate measurable business value.
• Rapidly iterate and deploy solutions within the constraints of active client engagements.
• Establish governance frameworks covering brand safety, content rights management, model selection, approval workflows, compliance, and auditability.
• Train and enable teams to successfully adopt new workflows and technologies.
• Define and track success metrics, including throughput, cycle time, cost-per-asset, quality consistency, and operational efficiency.
• Ensure knowledge transfer and long-term sustainability beyond the initial engagement.
• Contribute to project scoping and solution design across content operations, creative production, AI transformation, and marketing technology initiatives.
• Develop reusable accelerators, templates, tooling configurations, and best practices.
• Help evolve internal methodologies and delivery frameworks for future engagements.

Forward Deployed Engineer – AI, Creative Transformation

• Continue to develop, productize and maintain a business critical internal application for HPC/AI cluster design and simulation having dependencies on other internal critical applications.
• Use AI-assisted development tools (Claude, Gemini, etc.) to accelerate coding, prototyping, and problem-solving
• Participate in the full software lifecycle: design, implementation, testing, deployment, and maintenance
• Collaborate with HPC, infrastructure, and AI stakeholders to translate requirements into technical solutions
• Ensure performance, scalability, and reliability of the application
• Improve and automate development workflows using CI/CD best practices
• Contribute to code reviews, documentation, and knowledge sharing
• Continuously explore new tools, frameworks, and approaches to enhance productivity and product quality while maintaining production grade standards.

AI-Driven Application Developer – HPC/AI Tooling

• Design and build internal AI agents that automate workflows across teams such as Sales, HR, Customer Operations, and Finance
• Develop AI-powered tools and assistants that help Pelico teams work faster and make better decisions
• Build end-to-end AI workflows connecting LLM APIs, internal data sources, and operational systems
• Develop backend services and APIs (Python, FastAPI or similar) to support AI-driven internal tools
• Prototype and iterate quickly, shipping small AI applications that solve real operational problems
• Integrate AI systems with internal tools such as Slack, Notion, CRM systems, or internal databases
• Improve and maintain existing AI systems, debugging workflows and optimizing performance when things break
• Collaborate with internal teams to identify opportunities for automation and AI augmentation
• Contribute to Pelico’s internal AI stack, helping define best practices for building and deploying AI-powered tools

AI Ops Engineer

• Lancer et développer les activités commerciales sur le marché français
• Identifier, qualifier et conclure de nouvelles opportunités commerciales
• Développer et entretenir des relations solides avec les acteurs clés du secteur
• Gérer l’ensemble du cycle de vente, de la prospection à la signature des contrats
• Accompagner l’onboarding des nouveaux clients
• Représenter l’entreprise lors d’événements professionnels

Responsable Commercial – IA en Radiologie, Imagerie Médicale

• Design and ship local (on-device) AI models that run efficiently across gaming, biosensing, and peripheral applications.
• Work at the intersection of machine learning and real-time systems — taking models from prototype to optimized, production-grade inference that runs on the player's machine and our hardware, with tight latency and resource budgets.
• Implement and optimize AI/ML models for on-device inference in latency-sensitive gaming and peripheral contexts.
• Build and integrate models that process biosignal and sensor data (e.g. from peripherals and wearables) in real time.
• Optimize models for performance and footprint — quantization, pruning, and acceleration across CPU/GPU/NPU targets.
• Write efficient, production-quality C++ for the runtime and inference layers of our SDK.
• Collaborate with platform, haptics, and audio teams to expose AI capabilities to game studios through clean, well-documented APIs.
• Profile, benchmark, and continuously improve inference speed, memory use, and energy efficiency.

Senior AI Engineer

• Own AI research and end-to-end features
• Lead applied AI research and turn it into features shipped across our products
• Build evaluation harnesses (golden sets, regression tests) so AI features don't silently degrade
• Build the AI behind our usage analytics and the AI-driven strategic recommendations we provide to customers

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems
• Own production rollouts of consumer and internally facing GenAI applications
• Serve as a trusted technical advisor to customers across a variety of domains
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap

AI Engineer – Forward Deployed Engineer

• Build production agents — design, develop, and deploy goal-oriented AI agents and multimodal/conversational experiences using frameworks like Google ADK, Langchain, LangGraph, combined with orchestration tools like n8n where appropriate.
• Own the production lifecycle of what you ship — establish robust AIOps/AgentOps practices (monitoring, versioning of agent blueprints, evaluation pipelines, reliability) within your team's scope.
• Contribute to the shared Agentic Platform (Core pillar) — gateways, evaluation frameworks, observability, MaaS/AaaS APIs — so feature teams build faster on solid foundations.
• Build agent-side integrations (Feature pillar) — develop the MCP servers and backend services that agents need to interact with enterprise systems, in partnership with other R&D teams (and picking up the work yourself when a partner team doesn't have bandwidth).
• Be the Python referent in your team — own production-quality Python, enforce strong SWE principles (unit tests, CI/CD, Git, code review), and bring AIOps/MLOps best practices wherever you sit.
• Build a working expertise on agentic design patterns (eval, guardrails, multi-agent orchestration) and share it with AI champions and AI builders across the company as the GenAI Center of Expertise takes shape.
• Engage with stakeholders — talk to internal teams to understand operational pain points and translate them into measurable GenAI solutions. You don't lead cross-team architecture, but you should be credible across the org.

AI Engineer jobs in France

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AI Ops Engineer – F/H

Head of GenAI Platform

Consultant, AI Software Engineer, SDLC

Experienced AI Developer

Lead AI Engineer

Senior AI Developer

AI Engineer

Lead AI Engineer

Senior AI Developer

Développeur confirmé, IA

Forward Deployed Engineer – AI, Business Transformation

Forward Deployed Engineer – AI, Creative Transformation

AI-Driven Application Developer – HPC/AI Tooling

AI Ops Engineer

Responsable Commercial – IA en Radiologie, Imagerie Médicale

Senior AI Engineer

Senior AI Engineer

AI Engineer – Forward Deployed Engineer

AI Engineer, Freelance