Our client operates a digital marketplace for the CNC manufacturing industry, combining marketplace functionality with advanced AI-driven data intelligence. The platform enables companies to identify the best-fit contractors and make data-driven decisions across the CNC supply chain.The core product includes a chat-based B2B intelligence tool that delivers real-time operational and market insights powered by structured and unstructured data. We are looking for a Senior Azure DevOps Engineer to build and operate a production-grade AI and Data platform with focus on MLOps/DataOps automation, infrastructure-as-code, and production AI system reliability. This is a high-impact role with direct influence over AI infrastructure and platform evolution.
Requirements:
● 5+ years of hands-on experience as a DevOps/MLOps Engineer
● strong production-level experience with Azure services: Azure ML, Azure OpenAI, Microsoft Fabric, Databricks, Azure Container Apps, Azure Functions, Application Insights, Azure Policy, Azure Blob Storage, Azure SQL
● solid knowledge of Infrastructure as Code (IaC) using Terraform and/or Bicep for AI infrastructure provisioning
● practical experience with MLOps pipelines: CI/CD for ML models including training, validation, deployment, and monitoring (Azure ML, Databricks MLflow)
● experience with data pipeline automation: Fabric, Databricks, feature engineering workflows, data quality gates
● knowledge of observability and monitoring: model drift detection, data quality monitoring, API performance tracking (Application Insights, Prometheus)
● hands-on experience with GitOps workflows, Docker, Azure DevOps/GitHub Actions
● proficiency in Python, Azure ML SDK, Databricks APIs
● English — Upper-Intermediate (B2) or higher
What you will do:
● automate DataOps infrastructure: build and maintain data pipeline deployments (Fabric, Databricks), implement data quality gates, orchestrate feature engineering workflows
● manage infrastructure as code: provision and maintain AI infrastructure using Terraform/Bicep (Azure OpenAI, Fabric, Container Apps), implement GitOps workflows and environment management
● implement comprehensive observability: set up monitoring for model drift, data quality, and API performance using Application Insights and Prometheus
● build MLOps pipelines: create CI/CD workflows for ML models covering training, validation, deployment, and monitoring with Azure ML and Databricks MLflow
● automate AI governance: implement policy-as-code for responsible AI, automated compliance checks, and cost guardrails using Azure Policy and FinOps tooling
● optimize serverless orchestration: manage Azure Functions/Container Apps for AI workloads, optimize compute scaling, implement event-driven architectures
● ensure system reliability: achieve <1hr deployment cycles with automated quality gates for mission-critical AI systems
Why Rolique?
● we believe in fairness, transparency and helpfulness in everyday work
● your personal development is important to us, therefore we promote the internal transfer of knowledge and strengthen your "zone of genius"
● 20 days of paid vacation and 5 days of sick leave
● personal budget for courses, training, and certifications
● health support and sports compensation
● accounting support
