
Lead Backend Engineer
Role summary
We are seeking a Lead Engineer with 10+ years of experience to architect, design, and develop the PISCES HUB platform, a cloud-native, event-driven ecosystem for healthcare payer workflows. This role requires deep expertise in building metadata-driven systems, rule engines, and configurable integration frameworks, with a strong understanding of healthcare payment integrity, claims processing, and fraud detection. Responsibilities include technical leadership, mentoring teams, and ensuring system scalability and maintainability. The ideal candidate will have hands-on experience with Python/Java, AWS, Kafka, CI/CD, Docker, Kubernetes, and GitOps, along with specific knowledge of healthcare systems like Facets or QNXT.
Job Title: Lead Engineer
Location: STL/ Dallas
Experience Level: 10+ Years
Role Overview
We 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 Leadership
Lead 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 Design
Design 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
Design data models for:
Rule storage and versioning
Claims validation configurations
Payment integrity audit trails
Optimize SQL/NoSQL databases for high-volume rule evaluation.
Ensure rule governance, auditability, and compliance tracking.
Healthcare & Payment Integrity Domain Expertise
Strong understanding of:
Healthcare payer systems
Claims adjudication workflows
Pre-pay and post-pay validation logic
Payment Integrity rule frameworks
Fraud, Waste & Abuse detection concepts
Experience integrating with core healthcare systems (e.g., Facets, QNXT, Amisys or similar).
Ability to translate payment integrity business requirements into scalable technical design.
Cloud & Event-Driven Architecture
Design and implement event-driven systems using Kafka.
Build microservices deployed in AWS environments:
EKS, ECS, Lambda
S3, RDS, DynamoDB
Ensure high scalability and resilience for healthcare transaction workloads.
DevOps & Platform Engineering
Implement CI/CD pipelines with automated testing.
Containerize services using Docker and Kubernetes.
Apply GitOps workflows for deployment automation.
Ensure observability, monitoring, and production readiness.
Required Skills & Experience
8+ years of software engineering experience.
3+ years leading engineering teams or owning platform architecture.
Strong proficiency in:
Python or Java (both preferred)
Proven experience building configuration-driven systems.
Strong database modeling expertise (SQL & NoSQL).
Experience designing JSON/YAML/XML configuration interpreters.
Hands-on experience with Kafka and event-driven architecture.
Experience with AWS cloud services (EKS, ECS, Lambda, S3, RDS, DynamoDB).
Strong grasp of CI/CD, Docker, Kubernetes, and GitOps.
Strong knowledge of healthcare systems with focus on Payment Integrity.
Good to Have
Exposure to Machinify platform or similar AI-driven payment integrity systems.
Experience integrating rule engines with AI/ML-based fraud detection systems.
Experience building healthcare data hubs or enterprise integration platforms.
Ability to translate healthcare business rules into scalable technical solutions.
Ownership mindset with strong accountability.
Strong cross-functional collaboration and communication skills.
Ability to balance long-term platform vision with delivery timelines.
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