AI Architect – HealthTech Billing Solutions

Clarify AI is looking for an experienced AI Architect to lead the design and development of our end-to-end AI and machine learning infrastructure. In this role, you’ll build scalable, secure systems that power our healthcare billing solutions—from ingesting complex data to deploying explainable, production-grade models. You’ll work at the intersection of AI, healthcare, and real-world impact.

• Architect scalable AI/ML systems for both real-time and batch processing of healthcare billing data (e.g., claims, EOBs, medical codes).
• Design end-to-end data pipelines for structured and unstructured sources (e.g., PDFs, HL7, FHIR), from ingestion through feature engineering.
• Own the ML model lifecycle—from training and validation to deployment, monitoring, and re-training.
• Collaborate cross-functionally with data scientists, software engineers, and product managers to translate business needs into AI-powered solutions.
• Drive model explainability and fairness, ensuring compliance with healthcare regulations and building user trust.
• Ensure compliance with HIPAA, GDPR, and other privacy/security standards for handling sensitive health data.
• Evaluate and integrate third-party AI tools, including LLMs and APIs, when they can accelerate impact.
• Stay ahead of emerging technologies relevant to healthcare AI, and advise on strategic implementation.

• 5+ years of experience designing and deploying AI/ML systems at scale
• Strong foundation in machine learning, NLP, and modern AI system architecture
• Hands-on experience with healthcare data (claims, medical coding, EHRs, etc.)
• Expertise in cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, Kubeflow, Vertex AI, etc.)
• Proficiency in Python and experience with ML libraries (TensorFlow, PyTorch, Hugging Face)
• Familiarity with healthcare billing standards (CPT, ICD-10, UB-04)
• Experience with large language models and retrieval-augmented generation (RAG) pipelines
• Background in explainable and ethical AI development
• Experience in fast-paced, startup-like environments with cross-functional collaboration