AI Data Engineer Denial Prediction (Chennai)

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 510 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 Solid 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 preventionnot 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 .