AI Data Engineer – Denial Prediction

Job Title: Senior AI Engineer – Denial Prediction (RCM AI Platform)
Role Overview:
We are hiring a Senior AI Engineer to build and scale an AI-powered Denial Prediction
platform that proactively identifies prevents and explains claim denials across the RCM
lifecycle. This role focuses on combining AI-assisted software development (Copilot LLMs)
with predictive modeling and healthcare data engineering to drive measurable reductions in
denial rates.
You will architect systems that move beyond rule-based logic into intelligent learning-driven
workflows that integrate deeply with claims coding and payer behavior.
Key Responsibilities
• Design and develop AI-driven denial prediction systems using structured (837/835 EHR) and
unstructured healthcare data.
• Leverage AI-assisted development tools (GitHub Copilot LLM APIs) to accelerate feature
development and model deployment.
• Build predictive models to identify denial risk pre-submission (eligibility issues coding errors
payer-specific edits documentation gaps).
• Develop explainable AI outputs that clearly indicate why a claim is likely to be denied and
recommend corrective actions.
• Architect real-time and batch data pipelines for claims ingestion feature engineering and
model scoring.
• Integrate denial prediction engines into RCM workflows (coding billing claim scrubbing
edits).
• Continuously improve model performance using denial feedback loops (835 remits appeal
outcomes).
• Ensure HIPAA compliance auditability and traceability of AI-driven decisions.
• Establish validation frameworks for AI-generated code and model outputs.
• Collaborate closely with RCM SMEs to encode payer rules denial patterns and workflow
nuances into models.
Required Qualifications
• 5–10 years in software engineering with strong backend and data engineering experience.
• Hands-on experience using AI-assisted coding tools (GitHub Copilot ChatGPT etc.) in
production environments.
• Experience building or deploying machine learning models (classification anomaly detection
or risk scoring).
• Strong proficiency in Python (preferred) with experience in ML libraries (scikit-learn
TensorFlow PyTorch or similar).
• Experience working with healthcare data formats (X12 837/835 HL7 FHIR).
• Solid understanding of RCM processes especially claims submission and denial management.
• Ability to produce models (APIs pipelines monitoring retraining workflows).
Preferred Qualifications
• Experience building denial prediction claim scrubbing or revenue integrity solutions.
• Familiarity with payer rules engines and clearinghouse workflows.
• Experience with explainable AI techniques (feature importance SHAP rule extraction).
• Exposure to LLM-based reasoning for documentation validation or coding assistance.
• Experience integrating with EHRs (Epic Cerner) or billing systems.
• Understanding of HCC coding medical necessity rules and prior authorization impact on
denials.
Key Traits for Success
• Strong problem framing: can translate denial patterns into model-ready features.
• Balances speed (AI-assisted development) with precision (healthcare compliance).
• Obsessed with measurable outcomes (denial reduction % AR improvement).
• High ownership in building production-grade reliable AI systems.
• Thinks in feedback loops and continuous model improvement.
What Success Looks Like
• Reduction in denial rates pre-submission.
• Improved clean claim rate and first-pass acceptance.
• Actionable insights for coders and billers embedded in workflows.
• Scalable AI system that adapts to payer-specific behavior over time.
Why Join PAIX
• Build a category-defining AI product in denial prevention—not just analytics.
• Direct impact on hospital revenue and financial performance.
• Opportunity to shape AI-first RCM architecture from the ground up.
• Work closely with GTM and product to translate innovation into enterprise adoption