Senior AI Engineer (f/m/d)

About Decathlon

Decathlon aspires to become the world's best sports digital platform and open ecosystem. We want to enable customers to experience Decathlon through numerous local sports-centric experiences by connecting many third-party players and services, in a secure and efficient manner.

Our digital teams based in Lille and Paris (and more…) comprising over 5000 collaborators, are united to design and develop digital products with the objective of always offering the best value to our users. Present in over 70 countries, Decathlon is committed to innovation, sustainability, and customer satisfaction.

Job Description

Our PRISM (Supply Chain) team is looking for an AI Engineer based in Paris. As an AI Engineer dedicated to agent deployment, you will be at the heart of a tight-knit technical team. You will play a critical role in industrializing, deploying, and monitoring our agentic capabilities. You will work closely with digital teams (Data, Product, Engineering) to architect the deployment infrastructure, design intelligence routing, and build a secure infrastructure that allows our agents to interact natively with our company data and our legacy systems.

Responsibilities

• Design and deploy the solid foundations that will allow our AI agents to be hosted, executed, and interact seamlessly with our systems during production deployment.
• Design robust pipelines enabling multi-step asynchronous agentic execution (e.g., transactional ingestion and writing flows), by implementing distributed resilience patterns.
• Integrate agentic orchestration SDKs (especially Google Vertex AI Agent SDK / ADK), bypassing the "black box" limitations of managed frameworks.
• Efficiently orchestrate deployed agents while ensuring proper management of information processing, routing to the most suitable models, and guaranteeing optimal cost management and token usage. Ensure and guarantee the quality and speed of execution for the tasks to be performed.
• Strictly define the scope of action for each agent. You will guarantee that they only access the data and perform the actions for which they are formally authorized, in compliance with our privacy rules. By ensuring data security.
• Build advanced performance measurement and tracking pipelines to trace agent reasoning and decisions end-to-end in order to debug logic in production.
• Work with the team to define relevant and consistent data evaluation metrics in line with the defined specificities and functional metrics.

Skills

• Design of robust backends (Python), operational mastery of containerization (Docker, Kubernetes) and pipelines (CI/CD, automated testing, observability, log management) to ensure robust production deployments.
• Production-focused Python expertise, mastery of deployment platforms (Vertex AI Agent Builder, Gemini Enterprise Agent Platform) and client/server integration protocols like Model Context Protocol (MCP).
• Experience optimizing context windows for massive frontier models. Of request routing to models adapted to the solutions envisaged.
• Ability to build test frameworks for LLMs (LLM-as-a-Judge, Golden Datasets), mastery of deterministic metrics and strict validation of output formats (JSON schema enforcement).
• Hands-on experience with Agentic RAG, Semantic Caching to reduce latency and API costs, or using prompt optimization frameworks (e.g., DSPy).
• Applied experience in supply chain, retail, or model deployment via Databricks / MLFlow.

Attitude

• Excellent communication and collaboration skills.
• Ability to work effectively in a dynamic and fast-paced environment.
• Strong problem-solving skills and attention to detail.
• Adaptability and willingness to learn new technologies and methodologies and to share them.
• Ability to translate complex technical concepts into understandable terms for non-technical stakeholders.
• Ability to understand user challenges and associated needs.

Qualifications

• Senior Profile: You have solid experience (Machine Learning Engineering) with a strong orientation towards productionizing infrastructures.
• Ability to leverage managed solutions (Vertex AI) while knowing how to dive into details to fix distributed architectures, develop custom connectors, and bypass framework limitations.
• Demonstrated ability to evolve in changing technical environments.
• Operational ease on GCP and understanding of containerized environments (Docker, Kubernetes) to autonomously deploy the Agentic layer.

Technical Environment

• Agent orchestration: Gemini Enterprise Agent Platform, Vertex AI Agent Builder
• Infrastructures & Cloud: GCP (Google Cloud Platform), Docker, Kubernetes, CI/CD pipelines.
• AI & Integration Protocols: Model Context Protocol (MCP), LLMs (Gemini), LLM routing & memory management.
• Security & Access: Google Cloud Model Armor.
• Execution Engine: Databricks, AWS EKS, Sagemaker
• Payload: Python, Spark, Scikit-Learn, Tensorflow / Pytorch, Pyspark
• CICD: Github Actions
• Serving: Docker, Protobuf, gRPC
• Model registry, Model Tracking: MLFlow
• Orchestration: Airflow
• Documentation / code: Git, Confluence
• Data Visualization: Tableau

WHAT WE OFFER YOU

• 2 days of remote work per week;
• Equipment provided in accordance with your missions and our societal commitments (Mac, Windows, or Chromebooks);
• A local project team within a global network (possibility of international career);
• Skill development and support (diversity of projects, technical certifications from the first year, internal and external training, etc.);
• Remuneration package (employee profit sharing, monthly/quarterly bonuses).

Joining Decathlon means becoming part of a dynamic team passionate about sports, innovation, and making a positive impact on our customers' lives. If you are excited about leveraging data science to optimize supply chain processes and drive business growth, we invite you to apply and be part of our adventure.