AI Engineer--Office Based Raleigh North Carolina

Clinisys•Morrisville, NC

1d•$80,000 - $110,000•Onsite

About The Position

The AI Engineer (based in Raleigh, North Carolina) builds, releases, and operates AI solutions used across Clinisys. Working with AI Business Partners and teams throughout the company, the role turns real business needs into secure, reliable, and cost-effective solutions and keeps those solutions performing after launch. The AI Engineer also strengthens the shared tools, reusable patterns, integrations, and data foundations that allow Clinisys to deliver future AI solutions faster and more consistently.

Requirements

Strong software engineering fundamentals and hands-on AI or LLM solution experience.
Ability to work across application development, data engineering, cloud platforms, integration, and security.
Practical judgment in balancing solution quality, performance, reliability, safety, and cost.
Clear communication and disciplined documentation in a cross-functional environment.
Bachelor’s degree in Computer Science, Engineering, Data Science, a related field, or equivalent work experience.
3+ years in software, solutions, data, or cloud engineering, including at least 1 year building AI or LLM solutions.
Strong Python and/or C#/.NET skills, TypeScript, and SQL.
Hands-on experience with Azure AI Foundry, Azure OpenAI, Copilot Studio, or similar platforms.
Experience with RAG, prompt design, agents, API integration, data pipelines, and data modeling.
Familiarity with CI/CD, Git, infrastructure as code, cloud security, identity, and data privacy.

Nice To Haves

Experience with multi-agent orchestration, MCP servers, or evaluation frameworks.
Knowledge of networking, operating systems, compute, storage, identity, security, and cloud architecture.
Enterprise application development and integration experience.
Experience with scalable data processing, AI/ML services, and workflow orchestration.
Experience in healthcare, life sciences, or another regulated industry.

Responsibilities

Design and build AI solutions using agents, workflows, retrieval, and integrations.
Select models and technical approaches that balance quality, speed, and cost.
Build reusable components and contribute to solution standards.
Connect solutions to Microsoft 365, ServiceNow, CRM, ERP, APIs, and similar systems.
Bring in enterprise data and model it for reporting and AI use.
Make data available securely across the Microsoft ecosystem and related platforms.
Build tests and evaluations for quality, safety, and accuracy.
Apply security, privacy, identity, and access controls from the start.
Release solutions through repeatable pipelines with clear technical documentation.
Monitor, support, and improve solutions after launch.
Troubleshoot performance, reliability, integration, and cost issues.
Communicate status and outcomes to technical and non-technical stakeholders.