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

The Artificial Intelligence Engineer (AI Engineer) will design, develop, deploy, and integrate machine learning models, AI tools, and other analytics products into Alliance systems and workflows to improve member health, quality of services, and administrative processes. The AI Engineer will help to stand up the foundational platforms and processes that will facilitate development and sustainment of machine learning and artificial intelligence capabilities at Alliance now and into the future.

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

Build and Integrate Machine Learning and Artificial Intelligence Solutions

• Collaborate with technical managers and cross-functional teams to design, build, and deploy AI/ML models and solutions to improve care management, patient care decisions, and administrative processes. May include solutions leveraging descriptive analytics, predictive analytics, large-language models (LLMs), generative AI tools (GenAI), or prescriptive tools
• Analyze data, such as medical claims, electronic health records, and care management records, to understand patient care and business processes and identify opportunities for AI/ML to improve processes and care outcomes
• Develop specific analytics problem statements and modeling objectives from broadly defined care management and administrative use cases
• Iteratively develop data pipelines, AI/ML models, and supporting code to address analytics use cases
• Evaluate AI/ML models and tools – both internal (developed at Alliance) and external (developed by third parties) – with evaluation pipelines and appropriate metrics consistent with both modeling objectives and the intended health or process outcomes to be achieved with the tool
• Collaborate with application development, external vendors, and other internal IT teams to deploy and sustain AI/ML models and tools
• Design and implement model/tool monitoring reports or dashboards to disseminate information about model performance and impacts to stakeholders

Support Development of Platforms and Internal Processes for AI/ML Projects

• Collaborate with AI and IT leaders to establish and refine internal processes to govern development, evaluation, deployment, and sustainment of AI/ML tools
• Contribute to development of iternal and/or cloud-based infrastructure for development, evaluation, deployment, and monitoring of AI/ML tools
• Develop reusable resources, such as internal data processing or modeling libraries and reusable features, for use across AI/ML initiatives
• Adhere to all laws, regulations, internal policies, and ethical guidelines related to patient privacy, confidentiality, information security, etc., while developing AI/ML solutions

Communication and Collaboration

• Collaborate with cross-functional teams, including both technical and non-technical personnel, to execute AI/ML initiatives
• Communicate with subject matter experts within various functions inside Alliance to understand existing business processes, values, goals, opportunities, and constraints that will guide AI/ML development, integration, and evaluation
• Present results of analysis, model/tool evaluations, recommendations, etc., to technical and non-technical stakeholders
• Provide honest assessments of models, tools, AI/ML opportunities, and progress toward project goals to supervisors, collaborators, and other stakeholders within Alliance
• Support efforts to share knowledge about AI/ML tools, case studies, impacts, and opportunities internally across Alliance and, as deemed appropriate, with outside groups such as through industry group meetings

Continuous Learning and Professional Development

• Stay up to date on relevant AI and ML software, tools, modeling techniques, etc.
• Maintain awareness of AI/ML advances and use cases specifically relevant to managed care and other key Alliance functions

Minimum Requirements

Education and Experience

Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics or a related technical field and three (3) years of  experience developing and deploying software, machine learning, and/or artificial intelligence tools in a professional setting, including:

• Data wrangling and exploratory analysis of complex, real-world data
• Iterative development and evaluation of artificial intelligence and machine learning models
• Deployment, integration, and monitoring of AI/ML models and/or third-party AI/ML tools into production environment for internal or external use

Professional experience collaborating with non-technical stakeholders and/or users to define analytics problems based on open-ended business problem statements, interpret data and analyses, scope modeling activities, and evaluate AI or machine learning performance in the context of business outcomes. 

At least two (2) years of experience with Python and relevant libraries for data analysis, machine learning, and AI, such as pandas, Keras, and LangChain.

Preferred:

Master’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics or a related technical field.

Specific experience working with generative AI and large language models (LLMs).

Specific experience with medical claims, electronic health records, and other semi-structured medical data.

Experience using Azure Machine Learning, Azure AI Services and/or Databricks (e.g., Mosaic AI, AutoML).

Knowledge, Skills, & Abilities

• Strong technical expertise in AI/ML algorithms, data modeling, and data engineering.
• Fluency with Python and relevant libraries such as pandas, Keras, LangChain, etc.
• Ability to work with both structured (tabular) and unstructured (text, imagery, etc.) data sources for analysis and modeling.
• Good verbal and written communication skills, including the ability to explain analysis results and AI/ML modeling concepts, modeling approaches, and performance.
• Excellent analytical thinking, data analysis, and data visualization skills
• Experience with version control tools (e.g., git) and project management tools (e.g., Azure DevOps)
• Knowledge of medical claims data, electronic health records, and/or other healthcare-specific data sources
• Experience with large language models (LLMs) and generative AI models (GenAI), such as Llama and gpt-oss
• Experience with Azure Machine Learning, Azure AI Services, Databricks and/or comparable services
• Proficiency with SQL for querying structured data from relational databases