AI Dev OPS Engineer - hybrid - onsite 10-12 days a month

The AI DevOps is an integral part of Latham s Technology & Information Services team. This role will be responsible for designing, implementing, and managing automated deployment pipelines and supporting infrastructure for AI, ML, and agentic AI applications, while designing, building, implementing, and maintaining automated Azure DevOps CI/CD pipelines for AI/ML applications across development, testing, staging, and production environments. This role will be located in either our Global Services Office (Downtown Los Angeles) or New York office. Please note that this role may be eligible for a flexible working schedule that allows for a hybrid and in-office presence., Owning the application deployment lifecycle, including build automation, testing, security validation, containerization, artifact management, release promotion, deployment verification, and rollback procedures Developing and maintaining Azure DevOps YAML pipelines and reusable pipeline components in accordance with established firm procedures and engineering practices Working closely with AI Software Engineers, Machine Learning Engineers, and other development teams to understand application architecture, dependencies, hosting requirements, and operational considerations Working with Latham & Watkins internal infrastructure teams to define infrastructure requirements and support the provisioning and configuration of environments required for AI/ML applications Supporting application deployments across Microsoft Azure and on-premises virtual machines or virtual desktop infrastructure environments Protecting and maintaining any highly sensitive, confidential, privileged, financial, and/or proprietary information that Latham & Watkins retains

Demonstrate proficiency with Azure DevOps, including YAML pipelines, build and release automation, service connections, deployment environments, approvals, artifacts, variables, and access controls Exhibit strong understanding of CI/CD principles, automated deployment strategies, release management, DevSecOps practices, configuration management, and change-control processes Possess the ability to design reusable pipelines that automate application build, test, security validation, packaging, deployment, verification, promotion, and rollback activities

And have: A bachelor s degree in computer science, Information Systems, Engineering or related fields A minimum of five (5) years of industry experience in DevOps, cloud engineering, platform and infrastructure engineering, or application deployment A minimum of three (3) years of hands-on experience designing, building, and maintaining CI/CD pipelines using Azure DevOps Experience deploying and supporting containerized AI/ML, Generative AI, or data-intensive applications across Microsoft Azure and on-premises environments