Artificial Intelligence Operations Engineer (Full-time Hybrid, Morrisville, NC Based)

Alliance; United States; Hybride; USD 108 000 - 137 000; Plein temps

Avantages offerts par ce poste

Health, Dental, Vision

Life Insurance

Long Term Disability

Retirement Savings Plan

Flexible schedules (hybrid/remote)

Paid time off

Dress flexibility

Résumé du poste

Alliance is seeking an AI Operations Engineer for a full-time hybrid role based in Morrisville, NC. You will ensure operational stability, scale AI apps, and manage CI/CD pipelines for production models.

Responsibilities include observability, incident response, and collaboration with cloud and platform teams to optimize performance and cost efficiency.

Qualifications

• Bachelor's degree in Computer Science, Data Science, AI, or related field and 3+ years deploying AI/ML solutions.
• At least 2 years Python experience with ML libraries for development and deployment.
• Experience deploying AI models in production with CI/CD and MLOps practices.

Responsabilités

• Deploy, monitor, support, and maintain AI models in production environments with CI/CD.
• Develop and manage automated ML pipelines for packaging, testing, deployment, rollback, and lifecycle management.
• Architect hybrid cloud-AI environments supporting multi-model deployments.
• Implement IaC and automation for scalable AI services.
• Ensure observability with logging, metrics, tracing, and alerting; manage incidents promptly.

Connaissances

MLOps

LLMOps

IaC

Cloud Hybrid Azure

Observability

Containers

Python

Formation

Bachelor's degree in Computer Science or related field

Outils

Terraform

Ansible

Docker

Kubernetes

Azure

Description du poste

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Artificial Intelligence Operations Engineer (Full-time Hybrid, Morrisville, NC Based)

• Posted on October 14, 2026

Locations

Showing 1 location

Home Office
Morrisville, NC 27560, USA

• Hybrid
• Full-Time
• Requisition #: ARTIF003601

Description

The AI Operations Engineer is responsible for the operational stability, reliability, and continuous performance of deployed AI models and services. The AI Operations Engineer ensures that AI solutions built are seamlessly operationalized, monitored, and maintained in production environments. By managing the lifecycle of AI applications, from automated deployment and infrastructure scaling to real‑time monitoring and incident response, this role ensures that AI‑driven capabilities remain secure, cost‑efficient, and highly available to support Alliance Health’s mission‑critical clinical and operational workflows.

This position is full-time hybrid. Selected candidate must come into the Home office in Morrisville on Wednesdays, for business meeting as needed, reside within 50 miles of Morrisville North Carolina.

Responsibilities & Duties

AI Model Deployment & Infrastructure Operations

• Deploy, monitor, support, and maintain AI models in production environments, ensuring seamless integration with existing enterprise systems
• Develop and manage automated CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback, and full lifecycle management
• Architect and manage hybrid cloud-AI environments that support multi-model, multi-agent, and edge AI deployments
• Implement infrastructure automation using scripting, Infrastructure as Code (IaC), and configuration management to ensure scalable and resilient AI services
• Design and optimize AI infrastructure in collaboration with server, cloud, and platform engineering teams to support high-performance workloads

AI System Observability & Reliability

• Maintain comprehensive observability across all AI systems through advanced logging, metrics, performance monitoring, tracing, and alerting
• Detect and respond to critical operational risks, including model drift, performance degradation, and training-serving skew
• Define and monitor key operational metrics such as availability, latency, throughput, token consumption, model cost, and task‑completion rates
• Provide ongoing technical support, including rapid incident response, troubleshooting, and root cause analysis for AI platforms and user‑facing services
• Improve platform reliability, resilience, and cost‑efficiency through continuous tuning, automation, and operational improvements

AI Governance, Security & Compliance

• Partner with Cybersecurity, Risk, and AI Governance teams to implement and evidence required security controls
• Implement threat‑resistant AI infrastructure and enforce security frameworks to protect against data exfiltration and unauthorized access
• Ensure compliance with regulatory obligations and internal policies by maintaining model version control, audit trails, and lineage/traceability for data, prompts, and outputs
• Enforce data governance patterns, including privacy controls, data masking, and the secure management of secrets and identity across AI workflows

Operational Enablement & Collaboration

• Enable self‑service platform consumption for AI Engineers and Data Scientists via standardized APIs, reusable pipelines, templates, and documentation
• Collaborate across divisions to align technical implementations with mission‑critical business objectives and reduce operational disruption
• Communicate technical constraints such as latency, cost, and performance effectively to business stakeholders and technical leads
• Evaluate emerging AI tools, frameworks, and infrastructure approaches to determine their operational fit, supportability, and long‑term value for the organization
• Develop and maintain essential technical documentation, including runbooks, architecture diagrams, and standard operational procedures

User and Technical Support & Troubleshooting

• Provide hands‑on technical assistance to resolve issues arising from the integration of AI models into existing business workflows and systems
• Perform root cause analysis for technical failures in AI pipelines, including issues related to data integration, model performance, or infrastructure connectivity
• Support users in navigating technical complexities related to new AI platforms, tools, and orchestration frameworks to ensure minimal disruption to their operations

Education & Experience

Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field from an accredited college or university, and three (3) years of experience developing, implementing, and deploying software, machine learning, and/or artificial intelligence solutions. Experience must include integrating, deploying, monitoring, and maintaining AI/ML models and/or third‑party AI/ML tools within production environments for internal business operations and/or customer‑facing applications.

At least two (2) years of experience utilizing Python and related machine learning and artificial intelligence libraries and frameworks to develop, test, deploy, and support AI/ML solutions is required.

Knowledge, Skills, & Abilities

• MLOps & Model Lifecycle Management: Automating model deployment, testing, versioning, and rollback processes (CI/CD for ML).
• LLMOps & Generative AI Operations: Managing prompt configurations, evaluation pipelines, and lifecycle management for LLMs.
• Infrastructure as Code (IaC) & Automation: Using tools like Terraform or Ansible to deploy and manage cloud‑based AI infrastructure.
• Cloud & Hybrid Architecture: Managing compute resources and hybrid cloud environments (Azure) for AI workloads.
• Observability & Monitoring: Implementing logging, metrics, and alerting for model drift, latency, accuracy, and token consumption.
• Containerization & Orchestration: Docker and Kubernetes for scaling and managing AI microservices and agents.
• Programming & Scripting: Python, with familiarity with industry standard AI and ML libraries.
• AI Security & Governance: Implementing threat‑resistant infrastructure, IAM, encryption, and compliance within AI workflows.
• Technical Troubleshooting & Support: Ability to perform root cause analysis for complex integration issues and provide high‑level support to technical users.
• AI‑Augmented Productivity: Ability to utilize AI tools (GitHub Copilot) to accelerate operational tasks and documentation.

Employment for this position is contingent upon a satisfactory background check and credit check, which will be performed after acceptance of an offer of employment and prior to the employee's start date.

Salary Range

$107,607-$137,198/Annually

Exact compensation will be determined based on the candidate's education, experience, external market data and consideration of internal equity.

An excellent fringe benefit package accompanies the salary, which includes:

• 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

Qualifications

Education

Bachelors or better in Computer Science.

Equal Opportunity Employer

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