AI Engineer

Lyric is an AI-first, platform-based healthcare technology company, committed to simplifying the business of care by preventing inaccurate payments and reducing overall waste in the healthcare ecosystem, enabling more efficient use of resources to reduce the cost of care for payers, providers, and patients. Lyric, formerly ClaimsXten, is a market leader with 35 years of pre-pay editing expertise, dedicated teams, and top technology. Lyric is proud to be recognized as 2025 Best in KLAS for Pre-Payment Accuracy and Integrity and is HI-TRUST and SOC2 certified, and a recipient of the 2025 CandE Award for Candidate Experience. Interested in shaping the future of healthcare with AI? Explore opportunities at lyric.ai/careers and drive innovation with #YouToThePowerOfAI.

The AI Engineer is an ML engineer who is responsible for building and optimizing machine learning models, retrieval-augmented generation (RAG) systems, and verifiable ML systems that transform how we search and analyze complex medical and insurance data. This role requires a deep understanding of machine learning, LLM technologies, data science, and software engineering. This is an ML-engineering role and not a data science role, which means you should be comfortable building production-ready systems. This is not a research role.

This is a Hybrid role in the HYD office, 3 days a week.

Job Responsibilities

• Data engineering: Design and optimize systems capable of processing large volumes of data in both batch and real-time.
• Design, implement, and optimize retrieval-augmented generation (RAG) systems that leverage the latest LLM technologies to deliver highly relevant search results at scale.
• Develop and refine embedding models, vector databases, and retrieval mechanisms that maximize search relevance while minimizing latency and operational costs.
• Create robust evaluation frameworks to measure quality, continuously improve our LLM-based solution based on user feedback and performance metrics.
• Build and optimize machine learning models and verifiable ML systems that transform how we search and analyze complex medical and insurance data.
• Build and optimize production-ready systems that are scalable and can handle large amounts of data.
• Build and optimize agentic systems that can reason and make decisions.
• Develop machine learning models in healthcare and insurance settings with the highest standards for safety and quality.
• Stay on top of AI and ML security and governance requirements.
  
  

Basic Requirements

• BS in Computer Science (concentration on machine learning/AI), Engineering, Statistics, or a related field
• At least three (3) years of industry experience and specifically with some of the recent Gen AI technologies.
• Experience with containerization, Kubernetes, and cloud-native ML technologies such as Kubeflow.
• Experience with CI/CD pipelines and automated testing.
• High level of proficiency with Python and several ML frameworks.
  
  

Preferred Requirements

• Experience with medical coding and clinical policy analysis. Exposure to USA healthcare insurance will be an advantage.
• Strong understanding of clinical coding standards (e.g., ICD-10, CPT, HCPCS) is an advantage.