Senior Backend Architect

Revelation Pharma LLC•Remote, US,

36d•$150,000 - $175,000•Remote

About The Position

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 backend is where everything that matters actually happens. We are hiring a Senior Backend Architect to own the design and integrity of Grove’s backend transaction systems, data flows, and integration layer. This is an architect-practitioner role — you design the systems and you build them. You will define how data moves across the platform: from patient intake through clinical decision support, FHIR resource persistence, prescription dispatch, and AI agent orchestration. You will set the backend architecture standards that the KMS Technology engineering team executes against, and you will be the final authority on how Grove’s transaction systems are designed, integrated, and scaled. The ideal candidate has spent meaningful time architecting backend transaction systems at scale, has recent hands-on experience wiring agentic AI flows into production backend infrastructure, and understands what it takes to operate ML pipelines in a production healthcare environment. You know what a well-designed event-driven system looks like — and you know where the bodies are buried when it isn’t.

Requirements

5+ years of backend systems architecture experience — you have designed and shipped production transaction systems at scale, not just contributed to them
Recent hands-on experience architecting agentic AI or LLM-integrated backend systems — tool use, multi-step agent orchestration, state management, or prompt/response pipelines wired into production infrastructure
ML pipeline experience in a production environment — feature engineering pipelines, inference infrastructure, or model-serving integration; you understand the data flow from raw signal to model output to downstream system
AWS-native backend expertise — Lambda, EventBridge, API Gateway, RDS/Aurora, S3, IAM, Cognito; you design for AWS, not around it
FHIR R4 implementation experience — hands-on resource modeling and API work in a production system; clinical familiarity with Patient, MedicationRequest, Observation, CarePlan, and related resources
Event-driven architecture fluency — async workflow design, idempotency, dead-letter handling, saga patterns, and distributed transaction management
HIPAA-compliant architecture — PHI data handling, encryption at rest and in transit, audit logging, and access control in production healthcare systems
Strong TypeScript and/or Python; Node.js Lambda experience required

Nice To Haves

AWS HealthLake production experience — direct work with FHIR-native data stores at the infrastructure level
Canvas Medical or equivalent EHR integration (Athenahealth, Epic FHIR APIs) in a backend engineering context
Experience designing Markov-model or probabilistic state machine architectures in a clinical or behavioral context
AWS Bedrock experience — agent framework, knowledge base integration, or model invocation pipelines
Compounding pharmacy or e-prescribing system integration — DoseSpot, SureScripts, LifeFile, or equivalent
SOC 2 Type II audit preparation or equivalent compliance engineering experience
Experience as the backend architecture authority on a team that includes an offshore development partner

Responsibilities

Backend transaction system architecture — end-to-end data flow design across patient intake, clinical workflow, prescription dispatch, and care plan execution
FHIR R4 resource modeling and persistence — AWS HealthLake ingestion pipelines, resource lifecycle management, query optimization, and FHIR API contract design
Agentic AI integration architecture — designing the backend infrastructure that supports Grove’s six AI agents, including context management, tool-call orchestration, state handoff, and guardrail enforcement at the transaction layer
ML pipeline operations — infrastructure and data flow support for model training pipelines, feature stores, inference endpoints (AWS Bedrock, SageMaker), and model output integration into clinical workflows
Event-driven architecture — EventBridge / Lambda orchestration patterns for async clinical workflows, including prescription routing, refill logic, and care plan state transitions
PrescriptionDispatchService — the abstraction layer routing prescriptions between Innovation Compounding (LifeFile direct webhook integration), DoseSpot/SureScripts (Phase 2), and HiveRx (Phase 2)
Canvas Medical EHR integration — backend data synchronization, webhook handling, clinical workflow mapping, and FHIR resource exchange with the EHR layer
Backend integration contracts — API design, schema governance, versioning strategy, and integration standards across all Grove service boundaries
Infrastructure architecture — AWS service design (IAM, VPC, RDS/Aurora, API Gateway, S3, Cognito) with a security-first, HIPAA-compliant posture
Technical leadership of the KMS Technology engineering team on backend deliverables — architecture reviews, design docs, code review standards, and PR approval authority