AI Engineer - Llmops

Responsibilities:

• Perform code reviews for LLM-based applications, ensuring adherence to coding standards, security guidelines, and architectural best practices.
• Provide structured feedback to development teams to ensure compliance with enterprise standards.
• Deploy LLM applications across SIT, UAT, and Production environments using CI/CD pipelines.
• Design, implement, and manage Jenkins pipelines for automated build, test, and release processes.
• Utilise Databricks Asset Bundles (DAB) for packaging, versioning, and promoting assets across environments.
• Manage containerised deployments on Azure Kubernetes Service (AKS), including configuration, scaling, and cluster maintenance.
• Implement AKS deployment strategies using Helm charts and container orchestration best practices.
• Deploy and manage Snowflake applications, including database objects, role management, and environment migrations.
• Implement secure configuration management, secrets handling, and access control across environments.
• Monitor application performance and troubleshoot deployment-related issues.
• Provide L1 on-call support, including initial incident triage, basic troubleshooting, log analysis, ticket handling, and escalation to L2/L3 teams when required.
• Maintain deployment documentation, runbooks, and release standards across environments.

Requirements:

• We are looking for candidates with strong expertise in Azure, LLMOps, AKS (Azure Kubernetes Service), and Databricks.