Descripción de la oferta
Staff Interoperability Engineer (healthcare solution) Location: Remote from Spain (an indefinite Spanish employment contract) Intellias is looking for a Staff Interoperability Engineer to join a large-scale digital healthcare initiative focused on designing, building, and scaling healthcare interoperability solutions that enable secure, standards-compliant health data exchange across the U.S. healthcare ecosystem. This is a Staff-level Individual Contributor role for an experienced engineer who combines deep expertise in healthcare interoperability, distributed backend systems, API architecture, and cloud-native engineering. You will define technical direction, solve the platform's most complex interoperability challenges, and establish engineering standards that enable teams to build reliable, scalable, and compliant healthcare integrations. The role combines deep hands-on engineering with broad technical influence across interoperability architecture, FHIR implementation, API security, healthcare standards, and AI-enabled engineering practices. Project Overview: The project is building a FHIR-based healthcare data platform that enables secure interoperability across EHR systems, healthcare providers, payers, national healthcare exchange networks, laboratories, pharmacies, wearable devices, and digital health applications. The platform processes healthcare data at national scale, supporting Patient Access APIs, Bulk FHIR APIs, Provider Directory APIs, SMART on FHIR, and real-time healthcare integration services while maintaining compliance with U.S. healthcare interoperability standards and regulations. The engineering environment combines Python, Apache Spark, Kafka, Kubernetes, cloud-native infrastructure, FHIR R4, HL7, REST APIs, OAuth2/OIDC, SMART on FHIR, distributed event-driven architectures, and AI-assisted engineering. This is an AI-native engineering environment, where coding agents and reusable AI capabilities are used to accelerate implementation, testing, validation, documentation, and interoperability engineering without compromising correctness, security, or PHI safety. Requirements: 8+ years of professional experience in healthcare interoperability, Health IT, backend engineering, or distributed integration platforms. Proven Staff-level technical ownership of complex interoperability platforms and production healthcare integration solutions. 4+ years of hands-on experience implementing FHIR-based solutions, including production FHIR R4 implementations. Extensive experience integrating multiple EHR/EMR platforms, including systems such as Epic, Oracle Health (Cerner), Allscripts, athenahealth, eClinicalWorks, Meditech, NextGen, or comparable platforms. Proven experience implementing Patient Access APIs, Provider Directory APIs, Bulk FHIR APIs, and other FHIR-based interoperability services. Production experience integrating with HIE/HIN ecosystems, including Carequality, CommonWell, eHealth Exchange, TEFCA, or comparable national interoperability frameworks. Expert knowledge of FHIR R4, including resources, profiles, extensions, search parameters, Bundles, validation, and implementation patterns. Deep understanding of US Core Implementation Guides, USCDI, and U.S. healthcare interoperability requirements. Strong knowledge of SMART on FHIR, OAuth 2.0, OpenID Connect, SMART scopes, backend services, and healthcare authorization models. Strong understanding of HL7 v2.x, C-CDA, and healthcare data transformation patterns. Experience with healthcare terminology standards including SNOMED CT, LOINC, RxNorm, ICD-10, CPT, and CVX. Strong hands-on programming skills in Python, plus experience with at least one additional language such as Java, TypeScript/JavaScript, Go, or C#. Experience designing and building RESTful APIs, FHIR APIs, event-driven architectures, and distributed backend services. Strong knowledge of API security, including OAuth 2.0, JWT, mTLS, rate limiting, audit logging, and consent management. Experience with messaging technologies such as Kafka, RabbitMQ, or comparable event-driven systems. Experience building distributed systems using Spark, Kubernetes, Docker, and cloud-native infrastructure. Strong knowledge of ETL/ELT, CDC, streaming, and asynchronous processing patterns. Proven experience establishing reusable interoperability frameworks, engineering standards, implementation guides, and technical documentation. Practical experience using AI coding agents such as Claude Code or comparable AI-assisted engineering tools. Strong engineering judgment regarding deterministic processing versus AI-assisted implementation. Professional English sufficient for direct collaboration with U.S.-based engineering, product, and clinical stakeholders. Nice to Have: Experience with MPI (Master Patient Index), patient matching, identity resolution, or probabilistic matching algorithms. Experience with advanced clinical data-quality profiling and anomaly detection. Experience implementing healthcare consent frameworks such as FHIR Consent, XACML, DS4P. Experience with payer interoperability standards including CARIN Blue Button and Da Vinci Implementation Guides (PDex, CDex, HRex, DTR, PAS). Experience integrating healthcare wearable ecosystems such as Apple HealthKit, Google Fit, Fitbit, or comparable platforms. Experience integrating pharmacy standards such as NCPDP SCRIPT and Surescripts. Experience with laboratory interoperability including ORU/ORM messaging, LOINC mapping, DiagnosticReport. Experience building AI/LLM capabilities for clinical data extraction, terminology normalization, entity resolution, or healthcare interoperability. Contributions to HL7/FHIR communities, healthcare interoperability working groups, or open-source healthcare projects. Hands-on experience with HAPI FHIR, Synthea, or comparable interoperability frameworks. Responsibilities: Design, build, and scale large-scale healthcare interoperability solutions supporting secure, standards-based health data exchange. Define technical direction for FHIR implementation, API architecture, interoperability frameworks, and distributed integration services. Design and implement Patient Access APIs, Provider Directory APIs, Bulk FHIR APIs, and related interoperability services. Build integrations with EHR/EMR platforms, HIE/HIN networks, healthcare providers, payers, laboratories, pharmacies, wearables, and digital health ecosystems. Develop robust FHIR resource mappings, validation rules, transformation pipelines, and interoperability tooling. Design and implement HL7 v2.x to FHIR and C-CDA to FHIR transformation engines. Build automated frameworks for FHIR conformance testing, interoperability validation, data quality, and integration testing. Design secure healthcare APIs using SMART on FHIR, OAuth2/OIDC, JWT, mTLS, consent management, and modern API security practices. Solve complex interoperability issues involving API failures, patient matching, terminology normalization, data mapping conflicts, and compliance requirements. Define engineering standards, implementation frameworks, and reusable interoperability capabilities adopted across engineering teams. Make AI-assisted engineering a practical part of interoperability development, testing, documentation, mapping, and validation workflows. Mentor engineers through architecture reviews, technical guidance, pairing, and knowledge sharing. Represent interoperability best practices in architecture discussions and industry standards initiatives. Why this position: This role offers the opportunity to shape the technical direction of healthcare interoperability for a modern FHIR-based platform operating at national scale. As a Staff-level Individual Contributor, you will solve some of the most challenging interoperability problems in digital healthcare, including real-time data exchange, standards implementation, patient identity resolution, API security, healthcare compliance, and integration across thousands of healthcare organizations. The position combines deep healthcare interoperability expertise, distributed backend engineering, cloud-native architecture, API platform design, and AI-native engineering. Beyond building production systems, you will establish reusable engineering frameworks, define interoperability standards, mentor experienced engineers, and help shape how healthcare integrations are designed, implemented, validated, and operated across the platform.
