Lead end-to-end architecture, development, and delivery of APIs, microservices, and integration pipelines for internal and external healthcare systems, as well as 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, fostering a culture of innovation, ownership, and continuous learning, as well as step in as the escalation point for technical blockers, guiding the team toward solutions
Collaborate with Product, Architecture, Cloud, Security, and other engineering teams to define integration strategies and solution blueprints, as well as translate complex technical designs into clear communication for non-technical stakeholders
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

Requirements

Bachelor’s degree in relevant field; master’s degree preferred
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

Benefits

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Applicant Tracking System Keywords

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Hard Skills & Tools

API developmentmicroservicesintegration pipelinescloud-native solutionsMLOpsPythonNode.jsREST API designGraphQLevent-driven architecture

Soft Skills

leadershipmentoringcommunicationproblem-solvingcollaborationinnovationownershipcontinuous learningtechnical guidancetranslating technical designs

Certifications

Bachelor's degreeMaster's degree