The Data and AI Support Engineer you will be responsible for responsible for ensuring the stability, reliability, and optimal performance of data and Artificial Intelligence (AI)/Machine Learning (ML) solutions. Acting as the problem-solver for technical issues affecting data pipelines, databases, and deployed AI/ML models, ensuring continuous operation and high user satisfaction. Technical Expertise: Understanding of cloud computing concepts, specifically Microsoft Azure. Experience with Azure services like AKS clusters, App Services, Storage Accounts, Virtual Networks, Azure Active Directory, and Azure Monitor. Ability to support API based applications hosted on Azure. Familiarity with command-line interfaces (CLI) and scripting (PowerShell, Bash). Good handson experience on Python. Experience with monitoring tools and performance analysis. Proven experience with the Azure Python SDK and integrating Azure services - Storage, Key Vault, Logic App, Cosmos DB into software applications. Good Experience on supporting Python Based Web applications. Knowledge of LLM, Vector DB and RAG architecture will be a plus Basic understanding of networking concepts (TCP/IP, DNS, firewalls). Ability to troubleshoot software applications and their dependencies. Knowledge on supporting Data applications - ADB, ADF , Databricks, PySpark will be a huge plus. Knowledge on SQL is must. Understanding of PowerBI reports will be a plus. Communication and Collaboration: Effectively communicate complex technical concepts to both technical and non-technical audiences. Excellent problem-solving and analytical skills. Strong customer service orientation and empathy. Ability to work independently and as part of a team. Design and impact analysis · Contribute to define feasibility (technical options...), functional design and solution validation. · Performs impact analysis related to data captation (system performance in production, security, etc.) · Identifies the source of physical data · Enforces security and confidentiality rules for data on its perimeter Implementation and Deployment · Completes and executes data collection procedures · Builds data collection infrastructure (IoT: Internet of Things, sensors, database, files, etc.) · Deploys data collection infrastructure and procedures · Measures the impact on the technical chain implemented (from the connected object to the storage system) · Completes the necessary tests to validate the solution · Documents the implemented solutions Support and troubleshooting · Analyzes and understands the origin of a complex malfunction, incident or bug. · Adopts a proactive approach to avoid or identify root causes of problems. · Provides technical assistance to users.

About Michelin

Michelin is a world-leading manufacturer of life-changing composites and experiences. Pioneering materials science over more than 130 years, Michelin is uniquely positioned to make decisive contributions to human progress and a more sustainable world. Drawing on technological leadership in polymer composites, Michelin is constantly innovating to manufacture high-quality tires and components for critical applications in demanding fields as varied as mobility, construction, aeronautics, low-carbon energies, and healthcare. The care we put into our products and our intimate knowledge of consumer habits enable Michelin to offer its customers exceptional experiences, whether in terms of connected solutions and artificial intelligence for professional fleets, or for discovering the outstanding restaurants and hotels that the MICHELIN Guide recommends.