Principal AI Engineer

Description

 Principal AI Engineer

• Design and prototype AI-powered solutions using NLP, LLMs, and traditional ML techniques to: 
• Extract structured data from unstructured inputs (e.g., audio, transcripts, clinical notes)
• Evaluate and execute complex business and clinical decision logic
• Generate personalized recommendations using longitudinal member data
• Architect and lead the development of a centralized AI platform to support current and future AI use cases
• Design and implement secure, scalable data pipelines for both structured and unstructured healthcare data
• Select and customize appropriate models (LLMs, rule engines, hybrid approaches) based on business needs and regulatory constraints
• Collaborate with product, engineering, security, and compliance teams to ensure AI systems are explainable, auditable, and HIPAA-compliant
• Build internal tooling and workflows for data labeling, model evaluation, retraining, and lifecycle management
• Lead and mentor contract engineers and data scientists, ensuring PoC-to-production transitions are smooth and maintainable
• Document architecture, design decisions, model behavior, and performance metrics
• Stay current with AI/ML research, tooling, and regulatory developments, particularly in the healthcare domain

• 10+ years in software engineering, data science, or related technical roles
• 3+ years of hands-on experience building and deploying AI/ML-powered systems
• Proven track record delivering AI projects from prototype through production
• Strong expertise in MLOps, including model lifecycle management, CI/CD, and monitoring
• Deep experience with AI/ML tools, e.g., PyTorch, scikit-learn, Hugging Face
• Solid understanding of large language models (LLMs), prompt engineering, and vector search
• Ability to apply innovative solutions using LLMs and other emerging technologies
• Strong skills in model evaluation, testing, and validation in real-world applications
• Experience driving long-term technical roadmaps and establishing engineering best practices
• Experience working in healthcare or similarly regulated industries (e.g., finance, government)
• Knowledge of healthcare-specific standards (ICD, CPT, FHIR) and PHI data handling
• Familiarity with Microsoft Azure and its AI/ML services (e.g., Azure ML, Azure OpenAI)
• Experience implementing rule engines or clinical decision support systems
• Knowledge of AI observability, explainability, and risk management frameworks
• Excellent written and verbal communication skills          
• High attention to detail with ability to adapt and be flexible in a complex, changing environment
• A willing, effective, and efficient learner; willingness to receive feedback and take direction
• Ability to work remotely and travel occasionally for team meetings

To Apply:

To apply for this position or for more information about COPE Health Solutions, visit us at https://copehealthsolutions.com/careers/open-positions/.