Senior AI Engineer

Summary

Join Get Well as a Senior AI Engineer and contribute to the development and implementation of cutting-edge AI solutions in healthcare. Lead the design, development, and customization of large language models (LLMs) for critical healthcare applications. Collaborate with cross-functional teams to integrate scalable and secure AI systems into business processes. This role involves all phases of the AI development lifecycle, from data strategy and model development to production deployment and optimization. You will work with real-world structured and unstructured data, ensuring model outputs are actionable and trustworthy. The ideal candidate possesses 5+ years of hands-on experience with LLMs, ML, and related technologies, and a Master's degree in a relevant technical field.

Requirements

• Master’s degree in Computer Science, Artificial Intelligence, ML, or related technical field
• 5+ years of hands-on experience with: Training and fine-tuning LLMs
• Implementing multimodal AI solutions
• Working through the complete AI development lifecycle
• Developing AI solutions for complex domain use cases
• Technical proficiency in: Python programming and ML frameworks (PyTorch, TensorFlow, or equivalent)
• Fine-tuning techniques for LLMs (prompt engineering, PEFT, LoRA, etc.)
• Natural Language Processing (NLP) and Understanding (NLU) techniques
• Cloud computing and ML operations platforms
• MLOps, model deployment, and monitoring in cloud environments
• Experience with: Developing AI systems in regulated environments (e.g., healthcare)
• Real-world structured and unstructured data integration
• CI/CD for ML workflows, experiment tracking, and reproducibility tools
• KPI definition and performance evaluation frameworks
• Strong problem-solving skills and analytical thinking
• Ability to work effectively in fast-paced, agile environments
• Experience working with cross-functional teams
• Self-motivated with ability to work independently and collaboratively
• Excellent communication skills, both written and verbal
• Ability to explain technical concepts to non-technical stakeholders
• Strong documentation habits and attention to detail
• Collaborative mindset and team-oriented approach
• Adhere to all organizational information security policies and protect all sensitive information including but not limited to ePHI and PHI in accordance with organizational policy and Federal, State, and local regulations

Responsibilities

• Lead the design, development, and fine-tuning of large language models (LLMs) tailored for business-critical healthcare applications
• Apply domain adaptation techniques to foundation models for operational use cases
• Build multimodal AI systems that integrate structured and unstructured data sources
• Optimize model performance, accuracy, and efficiency for production environments
• Write clean, maintainable code for AI model training, evaluation, and inference at scale
• Build and manage data pipelines and MLOps frameworks for continuous learning
• Implement best practices for model versioning, experiment tracking, and reproducibility
• Integrate AI solutions with existing product architectures and infrastructure
• Prepare and process high-quality healthcare and operational data for model training and validation
• Apply privacy-preserving techniques and comply with healthcare data regulations (e.g., HIPAA)
• Implement synthetic data generation or augmentation strategies to enhance training datasets
• Address data quality issues such as class imbalance, sparsity, and noise in sensitive domains
• Design robust evaluation protocols and business-focused KPIs to assess AI model performance
• Monitor and improve fairness, transparency, and bias mitigation across AI solutions
• Conduct rigorous A/B testing, scenario simulations, and error analysis to ensure system reliability
• Track AI outcomes to support measurable gains in efficiency, accuracy, and user experience
• Partner with product and operations leaders to define AI requirements aligned with business goals
• Collaborate with domain experts to ensure model outputs are actionable and trustworthy
• Participate in agile development processes, including sprint planning and reviews
• Document solution architecture, modeling assumptions, and implementation processes
• Stay abreast of industry trends in LLMs, MLOps, and applied AI for business transformation
• Rapidly prototype and test emerging AI capabilities with practical business applications
• Contribute to internal tooling, frameworks, and reusable components for scalable AI development
• Proactively identify efficiency opportunities across business workflows through AI automation

Preferred Qualifications

• Basic understanding of healthcare data types and workflows
• Awareness of healthcare regulatory requirements (e.g., HIPAA, GDPR)
• Knowledge of responsible AI practices and ethical considerations
• Familiarity with healthcare terminology and patient care processes

Benefits

The estimated pay for this position is $145,000 - $200,000 in base salary plus bonus