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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.
