Artificial Intelligence Operations Engineer

Alliance Health

. Deploy, monitor, support, and maintain AI models in production environments .

Posted 10/14/2026full-timeMorrisville • North Carolina • United StatesMid-LevelSenior💰 $107,607 - $137,198 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in deploying and maintaining AI models in production environments, with a strong focus on MLOps, CI/CD pipelines, and infrastructure automation. Proficient in Python and familiar with AI security and governance practices.

Highest-signal resume keywords

MLOPSCI/CDPython ProgrammingInfrastructure As CodeAI Security

ATS Keywords

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Hard Skills

AI Model DeploymentMachine Learning SolutionsModel Lifecycle ManagementObservability ImplementationRoot Cause AnalysisPerformance MonitoringData IntegrationModel Drift DetectionCloud Architecture ManagementGenerative AI Operations

Soft Skills

Technical SupportCollaborationTroubleshootingProblem SolvingCommunication

Tools & Technologies

TerraformAnsibleDockerKubernetesAzureGitHub Copilot

Industry Keywords

AI InfrastructureHybrid CloudAutomation ToolsComplianceIAM

Tech Stack

Tools & technologies

AnsibleAzureCloudDockerKubernetesPythonTerraform

About the role

Key responsibilities & impact

Deploy, monitor, support, and maintain AI models in production environments
Develop and manage automated CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback, and lifecycle management
Architect and manage hybrid cloud-AI environments for multi-model, multi-agent, and edge AI deployments
Implement infrastructure automation using scripting, Infrastructure as Code, and configuration management
Design and optimize AI infrastructure with server, cloud, and platform engineering teams
Maintain observability through logging, metrics, performance monitoring, tracing, and alerting
Detect and respond to model drift, performance degradation, and training-serving skew
Define and monitor availability, latency, throughput, token consumption, model cost, and task-completion metrics
Provide incident response, troubleshooting, root cause analysis, and technical support for AI platforms and user-facing services
Improve platform reliability, resilience, and cost-efficiency through tuning, automation, and operational improvements
Implement security controls and threat-resistant AI infrastructure
Maintain model version control, audit trails, and lineage/traceability for data, prompts, and outputs
Enforce privacy controls, data masking, and secure management of secrets and identity
Enable self-service AI platform consumption through standardized APIs, reusable pipelines, templates, and documentation
Collaborate across divisions to align technical implementations with business objectives
Evaluate emerging AI tools, frameworks, and infrastructure approaches
Develop and maintain runbooks, architecture diagrams, and standard operating procedures
Provide hands-on assistance with AI model integration issues
Perform root cause analysis for failures involving data integration, model performance, or infrastructure connectivity
Support users with new AI platforms, tools, and orchestration frameworks

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field from an accredited college or university
Three (3) years of experience developing, implementing, and deploying software, machine learning, and/or artificial intelligence solutions
Experience integrating, deploying, monitoring, and maintaining AI/ML models and/or third-party AI/ML tools within production environments
At least two (2) years of experience utilizing Python and related machine learning and artificial intelligence libraries and frameworks
Knowledge of MLOps and model lifecycle management, including CI/CD for ML
Knowledge of LLMOps and generative AI operations
Experience with Infrastructure as Code and automation tools such as Terraform or Ansible
Experience managing cloud and hybrid architectures, including Azure
Experience implementing observability and monitoring for model drift, latency, accuracy, and token consumption
Experience with Docker and Kubernetes
Proficiency in Python and familiarity with industry-standard AI and ML libraries
Knowledge of AI security and governance, including IAM, encryption, and compliance
Ability to perform root cause analysis for complex integration issues and provide high-level technical support
Ability to utilize AI tools such as GitHub Copilot
Satisfactory background check and credit check required before employment begins
Must reside within 50 miles of Morrisville, North Carolina
Must be able to work in the Home office in Morrisville on Wednesdays and attend business meetings as needed

Benefits

Comp & perks

Medical, Dental, Vision, Life, Long Term Disability
Generous retirement savings plan
Flexible work schedules including hybrid/remote options
Paid time off including vacation, sick leave, holiday, management leave
Dress flexibility