Founding Backend Engineer

NxT LevelNew York, NY
Onsite

About The Position

Our client is hiring a Founding Senior Backend Engineer to own the data platform end-to-end and build the team around it. This is a true founding role: you will define canonical data models, ship the event backbone, enable analytics/experimentation, and create the integration architecture that makes adding EMR #5 configuration—not months of bespoke engineering. If you’re energized by unglamorous but high-leverage infrastructure (data modeling, pipelines, events, integrations), this is a rare seat.

Requirements

  • Systems-minded and data-opinionated: you treat data modeling as a craft and can explain why entities should relate a certain way
  • Comfortable with messy reality: you’re excited by pipelines, joins, ETL/ELT, and cleaning inconsistent third-party data
  • Event-driven by default: you’ve built (or deeply understand) real-time architectures, streaming/event backbones, and durable systems
  • Integration-savvy: you’ve shipped platforms that unify multiple external systems into clean internal abstractions
  • AI-native and curious: you naturally look for leverage (LLMs for parsing/structuring, automation for data QA, agent-based extraction when APIs don’t exist)

Nice To Haves

  • Experience with healthcare workflows, EMRs/EHRs, home health, or revenue-cycle concepts (authorization, billing, reimbursement)
  • Familiarity with healthcare data modeling standards (e.g., FHIR-style entity thinking)
  • Experience building experimentation frameworks or measurement systems tied to business outcomes
  • Background in data platform teams (data engineering + backend/platform) at high-growth startups

Responsibilities

  • Build the instrumentation layer that ties every agent decision to customer-level business metrics—e.g., client retention, caregiver satisfaction, authorization utilization, hours erosion. This becomes the foundation for experimentation, ROI claims, ML improvements, and product strategy.
  • Design an event-driven architecture where visit status changes, clock-ins, call-outs, ranking decisions, and workflow outcomes flow in real time—so internal systems (and future products) can consume events without constant EMR polling or rate-limit band-aids.
  • Create canonical data models across WellSky, HHAeXchange, AlayaCare, and Axxess so adding the next EMR is configuration-driven. This also unlocks revenue-cycle automation by enabling unified authorization and billing models.
  • Build the warehouse + tooling so engineers can answer: “Did this change improve customer outcomes?” quickly and consistently—without writing one-off queries every time.
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