AI Engineer/Data Scientist :: Hybrid Saint Louis Missouri :: Need Local candidate

Job ID: 28113686Reference Number: 26-00434Title: AI Engineer/Data Scientist :: Hybrid Saint Louis Missouri :: Need Local candidatePosted Date: 2026-04-30Contact: Ekta ChaudharyContact Email: View email address on click.appcast.io Phone: (551) 795-0621Company: HAN Staffing Only local candidate.Healthcare exp. Is must.Key search: Python, Oracle, Kafka, and Windsurf,GitHub Copilot or Cursor along with Payment Integrity platforms.Experience Level: 8+ YearsRole OverviewWe are seeking a highly skilled Lead Engineer to lead the architecture, design, and development of the PISCES HUB platform, a configuration-driven, event-based data and rule-processing ecosystem supporting healthcare payer workflows.This role requires strong expertise in building metadata-driven systems, rule engines, and configurable integration frameworks within a cloud-native architecture. The ideal candidate will also possess solid knowledge of healthcare systems, particularly Payment Integrity and claims processing workflows, and be capable of designing systems that support fraud detection, pre-pay/post-pay validation, and rule-based adjudication enhancements.Key Responsibilities Technical LeadershipLead end-to-end engineering for the PISCES HUB initiative.Provide architectural direction and hands-on leadership.Mentor development teams and enforce engineering best practices.Ensure scalability, configurability, and maintainability of rule-driven systems.Collaborate with Product, Payment Integrity SMEs, and Enterprise Architecture teams.Configuration-Driven System DesignDesign and build: Metadata-driven pipelines and workflow orchestration engines.Dynamic business rule engines for payment integrity use cases.Configurable API/data integration frameworks.Template-based or parameterized services.Develop JSON/YAML/XML-based configuration interpreters.Enable runtime rule updates without redeployment.Design version-controlled rule lifecycle frameworks with auditability.Data & Rule Configuration Modeling