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Dyania Health

Automates EMR review with AI

Mid/Senior Backend Engineer

Backend EngineeringConfirmed live in the last 24 hours
Full-timeAthens, GreeceNo salary listed

About the Job

Requirements

  • Proven experience as a backend software engineer working on data-intensive systems, ideally in healthcare, bioinformatics, or a similarly regulated domain.
  • Strong proficiency in Python, including async patterns and building services that process large data volumes.
  • Hands-on experience with event-driven or workflow-based architectures, such as queue/worker systems, pub/sub, durable workflow engines, or similar orchestrations of distributed, retryable jobs.
  • Solid experience with ETL, data transformation, and integration pipelines over heterogeneous sources.
  • Familiarity with SQL, including MSSQL and Postgres, and NoSQL data stores such as MongoDB, including schema and query-level performance tuning.
  • Experience with containerization using Docker, building and operating services in production, and CI/CD pipelines.
  • Strong debugging and systems-thinking skills, with the ability to reason about partial failures, idempotency, and retry semantics.
  • Clear written and verbal communication and comfort collaborating across clinical, AI research, and frontend teams.

Responsibilities

  • Design, build, and maintain event-driven backend components that power Synapsis AI's pipelines across multiple deployments.
  • Author and extend study-specific Python code that encodes clinical criteria, working closely with clinicians to translate protocols into executable matching logic.
  • Develop and optimize data models and storage layers covering structured clinical data and unstructured notes.
  • Implement and tune long-running, retry-safe workflows that coordinate CPU-bound and GPU-bound workers on shared infrastructure.
  • Contribute to the algorithmic reasoning engine that matches patient records against complex, time-sensitive trial criteria, in collaboration with the Clinical and AI Research teams.
  • Troubleshoot and improve performance, reliability, and observability of production deployments.
  • Document system designs, workflow contracts, and study definitions so new studies can be onboarded and new engineers can ramp up quickly.

Desired Qualifications

  • Experience with Temporal or a comparable durable workflow engine such as Airflow, Prefect, Argo Workflows, Cadence, or Step Functions.
  • Experience orchestrating GPU-bound inference work alongside CPU-bound services in a shared-resource environment.
  • Exposure to healthcare data standards such as HL7 and FHIR, or EHR analytics stores such as Epic Caboodle and Clarity.
  • Experience with vector databases or retrieval pipelines such as pgvector or FAISS.
  • Experience deploying to on-premises or private-cloud hospital environments, including HPC/Slurm or air-gapped contexts.
  • Experience authoring DSLs or declarative specification formats that non-engineers can read and validate.

About the Company

Dyania Health

Automates EMR review with AI

Dyania Health (Synapsis AI) automates the review and abstraction of electronic medical records (EMRs) by using AI together with medical expertise to interpret patient data and draw clinical conclusions. It analyzes EMR content to determine relevance and outputs structured data for tasks like pre-screening patients for clinical trials, conducting observational studies, and meeting reporting or registry requirements. The company stands out by blending domain-specific clinical knowledge with AI to handle complex EMR review across both clinical and research workflows, not just generic automation. Its goal is to help healthcare providers and research institutions operate more efficiently through automated EMR review and data extraction, typically via a service or subscription model priced by EMR volume and task complexity.

Company size
11-50
Company stage
Series A
Total funding
$17.6M
Headquarters
Jersey City, NJ
Founded
2019

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