What you will be doing:
- Lead end-to-end architecture, development, and delivery of APIs, microservices, and integration pipelines for internal and external healthcare systems.
- Act as the senior-most engineer for the team: designing components, writing high-quality code, troubleshooting complex issues, and performing rigorous code reviews.
- Build scalable, cloud-native solutions using Azure, containerized workloads (Docker/Kubernetes), and modern integration frameworks.
- Implement repeatable MLOps patterns for model deployment, monitoring, and lifecycle management.
- Build prototype PoCs that validate new technologies, workflows, or AI-enabled automations before scaling to production.
- Lead and mentor a team of engineers.
- Ensure all development aligns with HIPAA, PHI/PII-safe engineering, and healthcare interoperability requirements, as well as apply FHIR, HL7, EDI, and related healthcare interoperability patterns where applicable.
Experience you will need:
- Bachelor’s degree.
- Minimum of eight (8) years in software engineering, with at least three (3) years in a team leader or senior engineering capacity.
- Minimum of two (2) years of hands-on experience with AI/ML, Azure AI Foundry, AI Foundry agents, or related AI integration frameworks.
- Strong hands-on experience with Python and/or Node.js for API engineering and data integrations; known knowledge on Microsoft Azure tools stack is a must.
- Prior experience in healthcare, interoperability, or API-heavy environments is a must.
- Proficiency in REST/GraphQL API design, microservices patterns, authentication/authorization (OAuth2, JWT, Entra ID), and event-driven architectures.
- Familiarity with MLOps tools (Azure ML, MLflow, Databricks) and container ecosystems.
- Experience with interoperability standards such as FHIR, HL7, EDI, or clinical integration workflows is highly preferred.
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