Note: The job is a remote job and is open to candidates in USA. TalentXM is focused on enhancing healthcare through advanced AI solutions, and they are seeking a Senior AI Engineer. This role involves designing and building AI agents to automate revenue cycle management tasks, ensuring high accuracy and compliance with healthcare standards.
Responsibilities
- Design and build intelligent AI agents that use LLMs (GPT, Claude, and similar) to automate RCM tasks: claims scrubbing and submission, denial prediction and resolution, eligibility and benefits, and payment posting
- Build models that predict claim denials pre-submission, targeting the high-80s accuracy seen in the market
- Use Azure Cognitive Services (Form Recognizer, Text Analytics, Speech-to-Text, Translator) and Azure OpenAI, or AWS Bedrock, for document understanding and language tasks
- Apply retrieval-augmented generation so outputs cite the source and avoid invented claims
- Build end-to-end data pipelines for structured and unstructured healthcare data (claims, PDFs, EHR records)
- Stand up MLOps: model versioning, automated retraining, A/B testing, and real-time monitoring for drift as payer rules and coding change
- Define accuracy SLAs and the evaluation that proves them; feed outputs into the agents and the outcome dashboard
- Keep models and data inside HIPAA, SOC 2, and related security expectations
Skills
- 5+ years in AI/ML with production deployments, not just notebooks
- Deep experience with LLMs and NLP for text generation, classification, and unstructured-data analysis
- Hands-on with Azure Cognitive Services and Azure OpenAI, or AWS Bedrock
- Deep learning frameworks: PyTorch, TensorFlow, or Hugging Face Transformers
- Healthcare data standards: HL7, X12, FHIR, EDI, and RCM workflow knowledge
- Strong Python and RESTful API development
- MLOps: CI/CD for ML, model versioning, retraining, and monitoring
- Strong evaluation discipline: you can prove a model works and say when it does not
- RAG architectures, multi-agent or agentic systems, and prompt engineering at scale
- Automation platforms: Workato, UiPath, or Automation Anywhere
- Cloud-native distributed systems and latency optimization
- Open-source contributions, research, or patents in NLP or generative AI
- In-depth HIPAA and SOC 2 knowledge for AI in healthcare
Company Overview