Overview
The AI DevOps Engineer will play a critical role in establishing the engineering foundations necessary for deploying and operating AI solutions at enterprise scale within a leading global insurance organization. This position bridges the domains of DevOps, software development, and artificial intelligence, focusing on constructing CI/CD pipelines and automation processes tailored for AI products. The contractor will collaborate closely with AI, DevOps, and engineering teams to integrate Azure AI Foundry into the existing infrastructure and will be instrumental in creating reusable standards for deployment and governance.
Responsibilities
- Design and implement scalable CI/CD pipelines and deployment automation for AI-enabled applications and services.
- Integrate Azure AI Foundry and AI/GenAI services into enterprise DevOps and deployment processes.
- Build reusable Terraform Infrastructure-as-Code standards and modules, transitioning existing Bicep-based infrastructure to Terraform.
- Establish secure and governed deployment patterns, including DevSecOps controls and security scanning.
- Develop self-service deployment capabilities and standards that enhance consistency across environments.
- Support AI product teams across Azure, Docker, Kubernetes, and cloud-based platforms.
- Implement appropriate monitoring, logging, and observability across AI platforms and services.
- Identify opportunities to improve the SDLC through AI-enabled automation to enhance efficiency and quality of delivery.
Requirements
- Strong commercial experience as a DevOps/Platform Engineer with a software development background.
- Proven hands-on experience with Azure DevOps and CI/CD pipeline design and automation.
- Practical experience with Azure AI Foundry and deploying AI/GenAI solutions into production.
- Strong Terraform experience, ideally with reusable modules for enterprise-scale Infrastructure-as-Code.
- Understanding of the development, deployment, governance, and operation of AI solutions in an enterprise setting.
- Experience transitioning organizations from manual to automated, self-service delivery models.
- Proficiency in reading and understanding application code, with a development mindset.
- Experience with C# or Java is beneficial.