Elsevier
API Backend Developer
Philadelphia, Pennsylvania · Mid
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About the role
- You will focus on Kong API Management, backend API lifecycle (setup, testing, maintenance), HL7 FHIR, and enterprise integrations, primarily using Java and JavaScript.
- The ideal candidate has solid network fundamentals, can work comfortably with YAML (for declarative configs and pipelines), and thrives in pragmatic, production-oriented engineering-no frontend development in this space.
- It combines a massive curated medical knowledge base with conversational AI so clinicians can ask questions in natural language and get concise, clinically relevant responses backed by real scientific evidence.
Responsibilities
- Design & Build Distributed Services
- Building and maintaining a FHIR data facade that maps internal domain data to FHIR resources (read/search/transform), ensuring correctness and performance.
- Developing backend integrations with downstream systems (REST, gRPC, messaging/queues) and handle schema/contract evolution.
- Owning the API lifecycle: design (OpenAPI), implementation, automated testing (unit/integration/contract), versioning, and SLO-driven operations.
- Implementing OAuth2/OIDC flows, token introspection, and service-to-service auth. Apply secure coding practices and least-privilege network policies; partner with InfoSec on reviews.
Requirements
- 3+ years of Professional Experience in backend software engineering.
- working proficiency in JavaScript/Node.js.
- familiarity with FHIR resource modeling and transformations (e.g., Patient, Observation, Encounter).
Nice to have
- Implementing resilient, observable microservices and integration components (Java preferred
- Node.js/JavaScript where appropriate).
Skills
- Cloud & Ops: Experience deploying and operating services in a cloud or containerized environment (Docker/Kubernetes).
Benefits
- About the team, this team is building a generative-AI-powered clinical decision support tool designed specifically to help healthcare professionals quickly find trusted, evidence-based answers at the point of care.
This listing is sourced directly from Elsevier's careers page and normalized into a canonical job model.