We are now expanding our lab connectivity layer and are looking for a Lab Integration Engineer to own and scale integrations with national and regional diagnostic partners.

Role Overview

You will design, implement, and maintain integrations between beHuman and external laboratory systems (e.g., LabCorp, Quest, specialty diagnostics). This includes order routing, result ingestion, reconciliation, error handling, and long-term data normalization.

This role sits at the intersection of healthcare interoperability, engineering, and operations.

What You’ll Do

• Build and maintain HL7 v2 interfaces (ORM, ORU, ADT workflows)
• Implement FHIR-based integrations where available
• Manage lab order lifecycle (CPOE → requisition → results → reconciliation)
• Normalize LOINC-coded lab results into internal data models
• Design resilient pipelines for result ingestion and error monitoring
• Collaborate with clinical and revenue cycle teams on CPT/PLA code alignment
• Support TEFCA/QHIN data retrieval workflows post-appointment
• Build internal tooling for lab status tracking and exception management
• Document interface specs and maintain integration playbooks

Required Experience

• 3+ years of healthcare interoperability experience
• Strong experience with HL7 v2 (MLLP, message parsing, ACK handling)
• Experience with FHIR APIs (R4 preferred)
• Understanding of LOINC, CPT, and ICD-10
• Experience working with national labs or EHR integrations
• Familiarity with HIPAA-compliant system design
• Strong debugging and production support experience

Nice to Have

• Experience integrating with LabCorp, Quest, Natera, Guardant, Exact Sciences, etc.
• Knowledge of CMS billing workflows (PCM, E/M, PLA codes)
• Experience working with TEFCA/QHIN-based data exchange
• Background in oncology or screening workflows

What Success Looks Like

• Lab orders transmit reliably with a <1% failure rate
• Result ingestion is near real-time and fully structured
• Reduced manual reconciliation by >80%
• Scalable onboarding playbook for new lab partners
• Clean audit trail for payer and regulatory compliance

Tech Stack

• REST APIs
• HL7 interface engine (Mirth/NextGen or similar)
• Cloud-native architecture (AWS/GCP/Azure)
• Secure PHI-compliant pipelines

Why This Role Matters

Diagnostics are only useful if they move frictionlessly from order to insight to follow-up. You will be building the backbone that turns fragmented lab data into actionable screening programs at scale.