Senior AI Systems Engineer — Remote-Eligible MLOps Lead

ARA; Raleigh (NC); Hybrid; USD 150,000 - 210,000; Full time

Job summary

ARA is seeking a senior AI infrastructure engineer to lead deployment, integration, and operations of enterprise AI platforms across on-prem and cloud environments. You will design scalable AI infrastructure with server, cloud, and platform teams and operationalize ML workflows from development to production.

You will build robust CI/CD and MLOps pipelines, implement IaC automation, and provide ongoing support, logging, metrics, and incident response.

Qualifications

• Bachelor’s degree in computer science, engineering or related STEM field with 8-10 years of engineering experience.
• 2+ years supporting AI/ML platforms, MLOps workflows, model deployment, or AI-enabled infrastructure.
• Strong coding and automation skills in Python, Bash, or similar scripting languages.

Responsibilities

• Lead the deployment, integration, and operational support of AI platforms, tools, and services, ensuring compatibility with existing systems and enterprise processes.
• Design, implement, monitor, and optimize AI infrastructure, working with server, cloud, and platform engineering teams.
• Operationalize machine learning workflows and support AI-enabled applications from development through production deployment and sustainment.
• Build and maintain CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback, and lifecycle management.
• Implement infrastructure automation using scripting, Infrastructure as Code, and configuration management practices.
• Provide ongoing technical support, troubleshooting, root cause analysis, and documentation for AI platforms and user-facing AI services.
• Maintain observability across AI systems through logging, metrics, performance monitoring, alerting, and incident response practices.
• Ensure security, compliance, and governance requirements are met, including participation in audits, vulnerability management, and secure architecture reviews.
• Assess and implement system enhancements to improve performance, scalability, reliability, and cost efficiency.
• Collaborate across divisions to support diverse AI initiatives and align technical implementations with mission and business objectives.
• Evaluate emerging AI tools, frameworks, and infrastructure approaches for operational fit, supportability, and long-term value.
• Develop and maintain technical documentation, runbooks, architecture diagrams, and operational procedures.

Skills

AI platforms

Python

Bash

Kubernetes

CI/CD

MLOps

Security/compliance (NIST/CMMC)

Communication

Education

Bachelor’s degree in CS/Engineering or related field

Tools

PyTorch

Hugging Face

MLflow

Kubeflow

Job description

ARA is seeking a senior AI infrastructure engineer to lead deployment, integration, and operations of enterprise AI platforms across on-prem and cloud environments. You will design scalable AI infrastructure with server, cloud, and platform teams and operationalize ML workflows from development to production.

You will build robust CI/CD and MLOps pipelines, implement IaC automation, and provide ongoing support, logging, metrics, and incident response.