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Senior FHIR Developer

553b3b64 Bbe3 4ed0 B7c0 Bdb1b328dc09 9200659465994 2 · Remote, US · Remote · Active · $130,000–$165,000 / year · ADP Workforce Now Recruiting

Job facts

FieldValue
Company553b3b64 Bbe3 4ed0 B7c0 Bdb1b328dc09 9200659465994 2
TitleSenior FHIR Developer
Normalized title-
Department / team-
LocationUnited States
Work modelRemote / Remote
Employment typeFull Time
Salary$130,000–$165,000 / year
Statusactive
ATS providerADP Workforce Now Recruiting
Posted / first seen2026-06-01 / 2026-06-02
Changed / last seen2026-06-06 / 2026-06-06

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Linked records

Company553b3b64 Bbe3 4ed0 B7c0 Bdb1b328dc09 9200659465994 2
Sourcef9670fed-21ac-4f0d-9df0-b40eae7b3b03
ATS providerADP Workforce Now Recruiting

Description

About Evergreen Telehealth Evergreen Telehealth is a vertically integrated direct-to-consumer telehealth platform under Revelation Pharma Corporation — a PCAB-accredited, ASHP-accredited, LegitScript-certified compounding pharmacy group. We are building Grove, which is a transactional healthcare system — real prescriptions, real clinical workflows, real patients — and the FHIR is its core. The Role We are hiring a Senior FHIR Developer to own Grove’s FHIR data layer from resource design through system integration. This is a focused, deep specialty role. You will define how clinical data is modeled in FHIR R4 across every domain Grove touches — patient demographics, medications, observations, care plans, diagnostic reports, and clinical encounters — and you will build and maintain the integrations that make that data useful to the systems that depend on it. The two systems you will live inside are AWS HealthLake and Canvas Medical. HealthLake is Grove’s FHIR-native data store — you will own its resource schema, ingestion pipelines, and query surface. Canvas Medical is Grove’s ONC-certified EHR — you will program directly to the Canvas SDK, build and maintain clinical workflow integrations, and evolve how Canvas-sourced FHIR data is used across the rest of the platform. You will also define the FHIR contracts consumed by Grove’s AI agents, the Prescription Dispatch Service, and any downstream clinical analytics layer. If you have spent years doing real FHIR work — not reading the spec, not advising on it, not configuring a FHIR server someone else stood up — this is the role where that depth becomes the job. What You Will Own FHIR R4 resource schema governance — canonical definitions for every resource type Grove uses: Patient, Practitioner, Medication, Medication Request, Medication Dispense, Observation, Diagnostic Report, Care Plan, Goal, Condition, Encounter, Coverage, and Subscription resources AWS HealthLake data layer — ingestion pipeline design and maintenance, resource validation, search parameter configuration, bulk export for analytics and ML feature pipelines, and FHIR API contract ownership Canvas Medical SDK integration — direct programming to the Canvas SDK for clinical workflow automation, note creation, protocol execution, patient chart updates, and event-driven synchronization between Canvas and HealthLake FHIR data evolution — owning the roadmap for how Grove’s FHIR data model grows as new therapeutic verticals, clinical protocols, and platform capabilities are added; defining extension patterns, profiling strategy, and versioning standards AI agent FHIR contracts — defining the FHIR resource payloads consumed and produced by Grove’s six clinical AI agents, including the context structures passed to Bedrock and the structured outputs written back to HealthLake Prescription Dispatch Service FHIR interface — Medication Request and Medication Dispense resource design and lifecycle management across the LifeFile (Innovation Compounding), DoseSpot/SureScripts (Phase 2), and HiveRx (Phase 2) dispatch paths Subscription and webhook architecture — FHIR Subscription resource configuration for real-time clinical event delivery, and webhook payload schema design for inbound events from Canvas and LifeFile Data quality and conformance — resource validation rules, profile conformance testing, and ongoing data quality monitoring across the HealthLake data store FHIR API documentation and standards — internal developer-facing documentation for all FHIR contracts, resource profiles, and integration patterns; the reference layer that backend, mobile, and AI teams build against Technical collaboration with the KMS Technology engineering team — FHIR design reviews, resource modeling guidance, and integration standards enforcement on backend deliverables Other duties as assigned Non-Negotiable Requirements 4+ years of production FHIR R4 implementation experience — resource modeling, profiling, validation, and API development in live clinical systems; not configuration, not consulting, not spec familiarity AWS HealthLake hands-on experience — ingestion pipeline development, FHIR search parameter design, and data lifecycle management at the infrastructure level Canvas Medical SDK programming experience — direct integration development using the Canvas SDK; candidates without Canvas experience must have equivalent depth on a modern FHIR-native EHR (Epic FHIR R4 APIs, Athenahealth) and be able to demonstrate a clear ramp path Deep clinical resource fluency — you can model a GLP-1 titration protocol, a compounding pharmacy prescription lifecycle, or a longitudinal weight management care plan in FHIR R4 without referencing the spec FHIR Subscription and event-driven data flow experience — real-time clinical event delivery, webhook integration, and async data synchronization patterns HIPAA-compliant data handling — PHI field-level controls, FHIR-layer access scoping, audit log design, and data minimization in a production clinical environment Strong TypeScript or Python — you write the integration code, not just the specs Preferred Qualifications Experience defining FHIR resource contracts consumed by LLM or agentic AI systems — structuring clinical context for model input, and modeling structured clinical outputs back into FHIR resources US Core, Da Vinci, or other FHIR implementation guide profiling experience SMART on FHIR authorization and CDS Hooks integration experience Bulk FHIR export ($export operation) for ML feature pipeline or analytics use cases Compounding pharmacy or e-prescribing domain knowledge — Medication Request lifecycle, pharmacy workflow modeling, or DoseSpot/SureScripts integration experience Experience maintaining FHIR data quality in a system with multiple upstream write sources (EHR, patient-facing app, pharmacy system) Familiarity with ONC certification requirements and their implications for FHIR API design Benefits Health care insurance (medical, dental, vision) Life Insurance Supplemental Insurance PTO 401K matching Sick leave Phone/internet reimbursement Remote work

Full job record

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Last Seen At2026-06-06 13:29:59Z
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    "requisitionDescription": "<div><div style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;border:none;border-bottom:solid #1F4E79 1.0pt;padding:0in 0in 1.0pt 0in;' data-pasted=\"true\"><h2 style='margin-top:14.0pt;margin-right:0in;margin-bottom:7.0pt;margin-left:0in;font-size:16px;font-family:\"Arial\",sans-serif;color:#1F4E79;border:none;padding:0in;'>About Evergreen Telehealth</h2></div><p style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;margin-bottom:7.0pt;'>Evergreen Telehealth is a vertically integrated direct-to-consumer telehealth platform under Revelation Pharma Corporation &mdash; a PCAB-accredited, ASHP-accredited, LegitScript-certified compounding pharmacy group. We are building Grove, which is a transactional healthcare system &mdash; real prescriptions, real clinical workflows, real patients &mdash; and the FHIR is its core.</p><div style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;border:none;border-bottom:solid #1F4E79 1.0pt;padding:0in 0in 1.0pt 0in;'><h2 style='margin-top:14.0pt;margin-right:0in;margin-bottom:7.0pt;margin-left:0in;font-size:16px;font-family:\"Arial\",sans-serif;color:#1F4E79;border:none;padding:0in;'>The Role</h2></div><p style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;margin-bottom:7.0pt;'>We are hiring a Senior FHIR Developer to own Grove&rsquo;s FHIR data layer from resource design through system integration. This is a focused, deep specialty role. You will define how clinical data is modeled in FHIR R4 across every domain Grove touches &mdash; patient demographics, medications, observations, care plans, diagnostic reports, and clinical encounters &mdash; and you will build and maintain the integrations that make that data useful to the systems that depend on it.</p><p style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;margin-bottom:7.0pt;'>The two systems you will live inside are AWS HealthLake and Canvas Medical. HealthLake is Grove&rsquo;s FHIR-native data store &mdash; you will own its resource schema, ingestion pipelines, and query surface. Canvas Medical is Grove&rsquo;s ONC-certified EHR &mdash; you will program directly to the Canvas SDK, build and maintain clinical workflow integrations, and evolve how Canvas-sourced FHIR data is used across the rest of the platform. You will also define the FHIR contracts consumed by Grove&rsquo;s AI agents, the Prescription Dispatch Service, and any downstream clinical analytics layer.</p><p style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;margin-bottom:7.0pt;'>If you have spent years doing real FHIR work &mdash; not reading the spec, not advising on it, not configuring a FHIR server someone else stood up &mdash; this is the role where that depth becomes the job.</p><div style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;border:none;border-bottom:solid #1F4E79 1.0pt;padding:0in 0in 1.0pt 0in;' data-pasted=\"true\"><h2 style='margin-top:14.0pt;margin-right:0in;margin-bottom:7.0pt;margin-left:0in;font-size:16px;font-family:\"Arial\",sans-serif;color:#1F4E79;border:none;padding:0in;'>What You Will Own</h2></div><div style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;'><ul style=\"margin-bottom:0in;margin-left: 0in;\"><li style=\"margin:0in;font-size:15px;font-family: initial;\">FHIR R4 resource schema governance &mdash; canonical definitions for every resource type Grove uses: Patient, Practitioner, Medication, Medication Request, Medication Dispense, Observation, Diagnostic Report, Care Plan, Goal, Condition, Encounter, Coverage, and Subscription resources</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">AWS HealthLake data layer &mdash; ingestion pipeline design and maintenance, resource validation, search parameter configuration, bulk export for analytics and ML feature pipelines, and FHIR API contract ownership</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">Canvas Medical SDK integration &mdash; direct programming to the Canvas SDK for clinical workflow automation, note creation, protocol execution, patient chart updates, and event-driven synchronization between Canvas and HealthLake</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">FHIR data evolution &mdash; owning the roadmap for how Grove&rsquo;s FHIR data model grows as new therapeutic verticals, clinical protocols, and platform capabilities are added; defining extension patterns, profiling strategy, and versioning standards</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">AI agent FHIR contracts &mdash; defining the FHIR resource payloads consumed and produced by Grove&rsquo;s six clinical AI agents, including the context structures passed to Bedrock and the structured outputs written back to HealthLake</li></ul><div style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;' data-pasted=\"true\"><ul style=\"margin-bottom:0in;margin-left: 0in;\"><li style=\"margin:0in;font-size:15px;font-family: initial;\">Prescription Dispatch Service FHIR interface &mdash; Medication Request and Medication Dispense resource design and lifecycle management across the LifeFile (Innovation Compounding), DoseSpot/SureScripts (Phase 2), and HiveRx (Phase 2) dispatch paths</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">Subscription and webhook architecture &mdash; FHIR Subscription resource configuration for real-time clinical event delivery, and webhook payload schema design for inbound events from Canvas and LifeFile</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">Data quality and conformance &mdash; resource validation rules, profile conformance testing, and ongoing data quality monitoring across the HealthLake data store</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">FHIR API documentation and standards &mdash; internal developer-facing documentation for all FHIR contracts, resource profiles, and integration patterns; the reference layer that backend, mobile, and AI teams build against</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">Technical collaboration with the KMS Technology engineering team &mdash; FHIR design reviews, resource modeling guidance, and integration standards enforcement on backend deliverables</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">Other duties as assigned</li></ul><div style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;border:none;border-bottom:solid #1F4E79 1.0pt;padding:0in 0in 1.0pt 0in;' data-pasted=\"true\"><h2 style='margin-top:14.0pt;margin-right:0in;margin-bottom:7.0pt;margin-left:0in;font-size:16px;font-family:\"Arial\",sans-serif;color:#1F4E79;border:none;padding:0in;'>Non-Negotiable Requirements</h2></div><div style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;'><ul style=\"margin-bottom:0in;margin-left: 0in;\"><li style=\"margin:0in;font-size:15px;font-family: initial;\">4+ years of production FHIR R4 implementation experience &mdash; resource modeling, profiling, validation, and API development in live clinical systems; not configuration, not consulting, not spec familiarity</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">AWS HealthLake hands-on experience &mdash; ingestion pipeline development, FHIR search parameter design, and data lifecycle management at the infrastructure level</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">Canvas Medical SDK programming experience &mdash; direct integration development using the Canvas SDK; candidates without Canvas experience must have equivalent depth on a modern FHIR-native EHR (Epic FHIR R4 APIs, Athenahealth) and be able to demonstrate a clear ramp path</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">Deep clinical resource fluency &mdash; you can model a GLP-1 titration protocol, a compounding pharmacy prescription lifecycle, or a longitudinal weight management care plan in FHIR R4 without referencing the spec</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">FHIR Subscription and event-driven data flow experience &mdash; real-time clinical event delivery, webhook integration, and async data synchronization patterns</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">HIPAA-compliant data handling &mdash; PHI field-level controls, FHIR-layer access scoping, audit log design, and data minimization in a production clinical environment</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">Strong TypeScript or Python &mdash; you write the integration code, not just the specs</li></ul><div style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;border:none;border-bottom:solid #1F4E79 1.0pt;padding:0in 0in 1.0pt 0in;' data-pasted=\"true\"><h2 style='margin-top:14.0pt;margin-right:0in;margin-bottom:7.0pt;margin-left:0in;font-size:16px;font-family:\"Arial\",sans-serif;color:#1F4E79;border:none;padding:0in;'>Preferred Qualifications</h2></div><div style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;'><ul style=\"margin-bottom:0in;margin-left: 0in;\"><li style=\"margin:0in;font-size:15px;font-family: initial;\">Experience defining FHIR resource contracts consumed by LLM or agentic AI systems &mdash; structuring clinical context for model input, and modeling structured clinical outputs back into FHIR resources</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">US Core, Da Vinci, or other FHIR implementation guide profiling experience</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">SMART on FHIR authorization and CDS Hooks integration experience</li><li style=\"margin:0in;font-size:15px;font-family: initial;\">Bulk FHIR export ($export operation) for ML feature pipeline or analytics use cases</li><li style=\"margin:0in;font-size:15px;font-family: initial;\"><span style='font-size:15px;font-family:\"Arial\",sans-serif;'>Compounding pharmacy or e-prescribing domain knowledge &mdash; Medication Request lifecycle, pharmacy workflow modeling, or DoseSpot/SureScripts integration experience</span></li><li style=\"margin:0in;font-size:15px;font-family: initial;\">Experience maintaining FHIR data quality in a system with multiple upstream write sources (EHR, patient-facing app, pharmacy system)</li><li style=\"margin:0in;font-size:15px;font-family: initial;\"><span style='font-size:15px;font-family:\"Arial\",sans-serif;'>Familiarity with ONC certification requirements and their implications for FHIR API design</span></li></ul><p><br></p><div style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;border:none;border-bottom:solid #1F4E79 1.0pt;padding:0in 0in 1.0pt 0in;' data-pasted=\"true\"><h2 style='margin-top:14.0pt;margin-right:0in;margin-bottom:7.0pt;margin-left:0in;font-size:16px;font-family:\"Arial\",sans-serif;color:#1F4E79;border:none;padding:0in;'>Benefits</h2></div><div style='margin:0in;font-size:15px;font-family:\"Arial\",sans-serif;'><div style=\"margin-left:0in;\" data-pasted=\"true\"><ul style=\"list-style-type: disc;\"><li style=\"margin-left:0in;\">Health care insurance (medical, dental, vision)</li><li style=\"margin-left:0in;\">Life Insurance</li><li style=\"margin-left:0in;\">Supplemental Insurance&nbsp;</li><li style=\"margin-left:0in;\">PTO</li><li style=\"margin-left:0in;\">401K matching</li><li style=\"margin-left:0in;\">Sick leave</li><li style=\"margin-left:0in;\">Phone/internet reimbursement</li><li style=\"margin-left:0in;\">Remote work</li></ul></div></div></div></div></div></div></div>\n",
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