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The organization is seeking a professional specialized in Application Maintenance & Operations for Generative AI–based applications. The candidate will operate on complex, mission-critical, highly integrated enterprise solutions, built on Microsoft Azure infrastructure, with extensive use of AI services, microservices architectures, and containerized platforms. The objective of the role is to ensure operational continuity, application stability, security, and controlled evolution of AI solutions in production. This includes supporting runtime operations, monitoring, troubleshooting, tuning, and continuous improvement of distributed applications across multiple environments (e.g., Dev, Test, Prod). The role sits at the crossroads between the application layer and the infrastructure layer, with a strong focus on observability, system integration, data management, responsible use of AI resources, and strict adherence to security principles and access segregation.
Job Responsibility:
Manage corrective and adaptive maintenance activities for AI applications in production
Analyze and resolve application incidents and anomalies across front-end, back-end, and service layers
Support application release activities and configuration management across different environments (Dev/Test/Prod)
Collaborate with development teams to analyze application issues and improve overall software quality
Provide operational support for solutions based on Azure Kubernetes Service (AKS), including management of containerized workloads
Continuously monitor application and infrastructure services using Azure Monitor, Log Analytics, and Application Insights
Analyze application logs, metrics, and alerts to ensure appropriate levels of reliability and performance
Perform advanced troubleshooting on data ingestion pipelines, AI services, search services, and databases
Provide operational support for data persistence services, including Azure SQL Database for structured data, Azure Cosmos DB for unstructured data and conversational history, Azure Storage Accounts (Blob Storage) for document repositories
Verify and support correct content indexing and retrieval through Azure AI Search, including vector search and similarity search
Operate and monitor data preprocessing, transformation, and enrichment workflows (Transformation Layer)
Operate and manage application Managed Identities, ensuring adherence to the least privilege principle
Support secure handling of secrets and sensitive configurations using Azure Key Vault
Verify correct usage of AI services (e.g., Azure OpenAI, LLMs, embeddings, cognitive services) according to architectural governance and policies
Collaborate with security teams to ensure compliance with network and security requirements (no public exposure, access via internal network/VPN)
Contribute to the evolution of AI solutions with a focus on scalability, reliability, and cost optimization
Propose improvements to logging, monitoring, and application feedback mechanisms
Support the go-live and stabilization of new Generative AI use cases, aligned with reference architectures
Requirements:
Experience in Application Maintenance and Operations for enterprise applications
Solid knowledge of Python in an application context focused on AI functionalities
Operational knowledge of Microsoft Azure and its main PaaS services
Experience with Azure Kubernetes Service (AKS) and containerized workloads
Strong troubleshooting skills based on logs, metrics, and alerts
Knowledge of monitoring, logging, and observability principles
Familiarity with microservices architectures and multi-layer environments
Understanding of IAM concepts, Managed Identities, and secret management
Experience operating AI / Generative AI solutions in production
Knowledge of Azure OpenAI, embedding services, and vector search
Experience with Azure AI Search, Cosmos DB, and Document Intelligence
Familiarity with ITIL operational models (Incident, Problem, Change Management)
Experience in highly critical and security-sensitive enterprise environments
One or more Microsoft AI certifications (e.g., Microsoft Certified: Azure AI Engineer Associate – AI-102)
Strong analytical and problem-solving mindset
Ability to work in cross-functional teams (development, architecture, security)
Structured, quality-driven approach to service delivery
High level of autonomy and responsibility in managing production environments
Strong technical communication and documentation skills
Nice to have:
Experience operating AI / Generative AI solutions in production
Knowledge of Azure OpenAI, embedding services, and vector search
Experience with Azure AI Search, Cosmos DB, and Document Intelligence
Familiarity with ITIL operational models (Incident, Problem, Change Management)
Experience in highly critical and security-sensitive enterprise environments
One or more Microsoft AI certifications (e.g., Microsoft Certified: Azure AI Engineer Associate – AI-102)