AI DevOps Engineer – Global

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop, maintain, and enhance CI/CD pipelines for the deployment of AI and machine learning solutions.

• Implement and oversee containerized AI applications utilizing Docker and Kubernetes.

• Monitor production settings, model efficiency, infrastructure wellness, and system dependability.

• Work collaboratively with AI engineers, data scientists, and solution architects to optimize deployment workflows.

• Apply Infrastructure-as-Code methodologies to boost scalability, uniformity, and replicability.

• Oversee cloud infrastructure and platform services across AWS, Azure, and GCP environments.

• Uphold security, compliance, and access control protocols for AI systems.

• Diagnose infrastructure and deployment challenges while aiding incident response initiatives.

• Develop and sustain operational documentation, deployment protocols, and technical runbooks.

• Enhance observability, monitoring, logging, and alerting systems for AI platforms.

⛳️ Requirements

• Practical experience in deploying and managing machine learning models within production settings.

• In-depth knowledge of containerization technologies and orchestration platforms.

• Proven experience in constructing and maintaining CI/CD pipelines.

• Hands-on experience with Infrastructure-as-Code tools and cloud-native environments.

• Familiarity with monitoring, logging, and observability solutions.

• Strong grasp of security best practices for cloud and AI infrastructure.

• Exceptional written and verbal communication skills in English.

• Capability to operate independently in a fully remote, U.S.-aligned setting.

• Strong troubleshooting, problem-solving, and interdisciplinary collaboration skills.

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related discipline is preferred, or equivalent professional experience.

• At least three (3) years of experience in DevOps, MLOps, platform engineering, or related infrastructure roles.

• Experience with government, education, or other regulated public sector organizations is preferred.

• Familiarity with compliance frameworks such as FedRAMP, NIST, or similar regulatory standards is preferred.

• Experience in supporting LLM deployment pipelines, generative AI infrastructure, or AI platforms is preferred.

• Experience with MLOps frameworks and model lifecycle management is preferred.

• Cloud certifications, including AWS, Azure, or GCP, are advantageous.

• Background in consulting or client-facing technical environments is preferred.

🏝️ Benefits

• Flexible paid time off

• 5% 401K matching program

• Equity opportunities

• Incentive and bonus programs

• Up to 16 weeks of paid parental leave

• Flexible spending accounts

• Comprehensive health benefits with base employee coverage fully funded, including:

• Medical, dental, and vision coverage

• Life insurance

• Short and long-term disability coverage

• Income protection benefits