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# AI DevOps Engineer

- **Company:** Robert Half
- **Location:** Los Angeles, CA, United States
- **Salary:** $160,000.0 - $185,000.0
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, DevOps, Distributed Systems, Github, Performance Tuning, Google Cloud, Delivery Pipeline, Grafana, Reliability of Systems, Containerization, AI Platforms, Infrastructure Automation Frameworks
- **Published:** June 4, 2026
- **Apply:** https://www.dice.com/job-detail/b8d787c3-5617-400f-b1ed-9f6f26f7c444

## About the Role

* Strong experience building and managing CI/CD pipelines (e.g., GitHub Actions or similar)
 * Hands-on experience with major cloud platforms (AWS, Azure, or Google Cloud Platform)
 * Experience with infrastructure automation and containerization concepts
 * Knowledge of AI/ML deployment workflows and operational best practices
 * Strong understanding of system reliability, monitoring, and observability tools
 * Experience implementing secure infrastructure and access control frameworks
 * Excellent communication skills with the ability to collaborate across technical and business teams

Preferred Qualifications (Nice-to-Haves)

 * Experience supporting or deploying generative AI platforms in production environments
 * Familiarity with AI cost management and performance optimization strategies
 * Background in scaling enterprise-grade distributed systems
 * Experience mentoring or leading engineering initiatives
 * Exposure to AI governance and compliance frameworks

## Description

The AI DevOps Engineer will play a critical role in designing, deploying, and scaling AI-driven systems in a production environment. Based in Los Angeles, CA, this position focuses on building robust CI/CD pipelines, enabling reliable AI operations, and ensuring secure, scalable infrastructure. This role partners closely with both technical and business stakeholders to operationalize AI solutions and drive enterprise-wide adoption., * Design and implement CI/CD pipelines for AI applications and services

 * Build and manage scalable AI deployment frameworks and infrastructure
 * Establish best practices for AI operations, including monitoring, reliability, and cost optimization
 * Automate infrastructure provisioning and configuration using modern DevOps tools
 * Develop observability solutions to ensure high system performance and uptime
 * Implement secure deployment practices and maintain strong access controls
 * Operationalize AI platforms and integrate them into business workflows
 * Collaborate with cross-functional teams to identify opportunities for AI-driven scaling
 * Educate internal stakeholders on AI capabilities, tools, and operational best practices
 * Contribute to long-term infrastructure and AI platform strategy


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