Principal Azure DevOps Engineer

Our customer is a leading organization undergoing digital transformation, specializing in implementing advanced AI solutions across their business operations. They're committed to leveraging cutting-edge technology to drive innovation and efficiency.

The customer is currently undergoing a significant Cloud transformation journey, migrating from on-premises infrastructure to cloud-based solutions. This project involves building  scalable infrastructure to support their AI/ML initiatives, ensuring seamless deployment and operation of machine learning models in production environments.

You'll be joining a collaborative team of DevOps engineers, data scientists, and ML engineers focused on creating and maintaining the infrastructure that powers the organization's AI solutions. The team values innovation, technical excellence, and continuous improvement in delivering secure, efficient, and scalable AI systems.

• Interview process that respects people and their time
• Professional and open IT community
• Internal meet-ups and resources for knowledge sharing
• Time for recovery and relaxation
• Bright online and offline events
• Opportunity to become part of our internal volunteer community

• Design, implement, and maintain CI/CD pipelines for AI/ML application deployment using Azure DevOps
• Architect and lead the migration from on-premises infrastructure to cloud-based solutions in Azure (or AWS)
• Create, optimize, and manage Docker containers specifically designed for AI/ML services and workloads
• Implement infrastructure-as-code using Terraform or ARM templates for reproducible deployments
• Develop and maintain Kubernetes configurations for orchestrating microservices in AKS
• Build scalable, self-healing infrastructure for ML model training and inference
• Establish monitoring, logging, and alerting for AI systems using Application Insights
• Optimize cloud resource utilization and costs for compute-intensive ML workloads
• Implement automated testing and validation for ML model deployments
• Design and implement secure API gateways for AI services
• Collaborate with data scientists and ML engineers to streamline the model development-to-production lifecycle
• Ensure security best practices and compliance requirements are implemented across all infrastructure
• Automate performance optimization for large-scale data processing pipelines.

• Strong experience with Microsoft Azure services, particularly:
  • Azure Kubernetes Service (AKS)
  • Azure App Services
  • Azure DevOps CI/CD pipelines
  • Azure Container Registry
  • Azure Application Insights
  • Azure Machine Learning service
  • AWS knowledge (ECS, ECR, Lambda, EKS) is acceptable as an alternative
• Expertise in containerization and orchestration:
  • Docker container development and optimization
  • Kubernetes cluster management and deployment strategies
  • Experience with scaling containerized ML/AI workloads
• CI/CD implementation for ML pipelines using Azure DevOps or GitHub Actions
• Proficiency in Python for:
  • Infrastructure as Code (IaC) using Terraform or ARM templates
  • ML/AI deployment automation
  • Monitoring and logging solutions for AI systems
• Experience with RESTful APIs, GraphQL, and microservices architectures
• Understanding of ML/AI specific deployment requirements:
  • Model versioning and A/B testing infrastructure
  • GPU/compute optimization for ML workloads
  • ML model monitoring and performance metrics
  • Handling large-scale data pipelines for AI training and inference
• A proactive problem-solver who identifies infrastructure challenges before they become issues
• Someone who takes ownership of solutions rather than waiting for detailed instructions
• Passionate about DevOps practices and modern infrastructure approaches
• Self-motivated with a drive to continuously improve systems
• A clear communicator who can translate technical concepts for various stakeholders