Epic Systems Application Support Engineer

Owns the strategy, roadmap, lifecycle, and commercial performance of externally sold fraud detection and prevention products. Defines fraud capabilities, KPIs, business cases, and product requirements while partnering with data science, engineering, risk, compliance, operations, and external vendors. Evaluates detection methods, market trends, fraud typologies, regulatory expectations, and product performance to guide investment, operational readiness, adoption, and risk mitigation.

Designs, develops, and deploys AI/ML and generative AI solutions for healthcare claims, including fraud detection, overpayment disputes, workflow automation, and document understanding. Builds LLM applications, RAG frameworks, and prompt engineering solutions; develops evaluation and validation processes; optimizes model deployment and inference; and supports responsible AI governance. Collaborates with engineering, product, analytics, data science, and business teams to deliver scalable solutions and measurable operational improvements.

Develop and maintain scalable enterprise data pipelines and ETL/ELT workflows using Python, PySpark, Databricks, Snowflake, Azure Data Factory, and related technologies. Support batch and streaming workloads, cloud data movement, platform stability, incident resolution, security remediation, upgrades, and operational support. Build AI tools, optimize data platforms, collaborate across teams, and contribute to documentation and continuous improvement within healthcare data environments.