Cloud & AI Engineer

Basic Qualifications

- Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline; or six years of relevant equivalent experience.
- Three or more years of experience supporting cloud, data, AI, machine-learning, software, or hybrid technology environments.
- Experience with Microsoft Azure services and cloud infrastructure concepts, including identity, networking, security, compute, storage, and monitoring.
- Experience developing, deploying, supporting, or integrating data, analytics, machine-learning, or AI solutions.
- Ability to work effectively with technical and non-technical stakeholders in a manufacturing or enterprise environment.
- Willingness and ability to travel up to 25% as required.
- Employees must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.
- This position may require access to export-controlled technology; therefore, candidates must be a U.S. person as defined by U.S. export-control laws.

Preferred Qualifications

- Experience with Azure Machine Learning, including model training, registration, managed endpoints, pipelines, monitoring, and MLOps practices.
- Experience with Azure AI Foundry, Azure OpenAI, Azure AI services, prompt engineering, model evaluation, and responsible-AI controls.
- Experience designing Azure architectures that integrate cloud, on-premises, enterprise, and operational technology environments.
- Experience operationalizing machine-learning or AI models for production use, including deployment automation, model monitoring, drift detection, versioning, and rollback approaches.
- Familiarity with secure integration patterns and data flows involving process-control, manufacturing, industrial, or operational technology environments.
- Experience with Azure DevOps, Git, CI/CD pipelines, PowerShell, Python, Terraform, ARM templates, or other automation and infrastructure-as-code tools.
- Knowledge of Microsoft Entra ID, Azure networking, private endpoints, role-based access control, logging, monitoring, and security best practices.
- Experience with data platforms, APIs, message-based integrations, SQL, data pipelines, or data-lake architectures.
- Strong troubleshooting, analytical, organizational, written, and verbal communication skills.
- Ability to work independently while contributing effectively in a collaborative, cross-functional team environment.