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Salary
≈ $49k – $94k per year (Estimated)
Location
Hybrid (Athens, Greece)
Seniority
Senior
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 5, 2026. First seen by Alion on May 4, 2026. Dyania Health scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Synapsis AI automates chart review and abstraction with >95% accuracy. Unlock EMR data at scale, with unprecedented insight.

About Dyania Health

Dyania was born with the mission to find clinically critical and relevant insights buried within electronic medical records and release these insights to inform and drive clinical care and clinical research. Our vision is to make sure every patient gets the right care at the right time based in medical decisions precisely informed by their own data. Each patient’s medical record would take a provider nearly 2 hours to read once, let alone read again and again for all the updates cumulated over time. It would be humanly infeasible to achieve even if there was an army of available human clinicians with time that they could spare. Moreover, if so much of medicine is undiscovered, how is an AI model meant to reason appropriately if humans do not know or agree on the right answer? What does high performing reasoning mean in a world of discord and vagueness?

Synapsis AI is the answer.

At Dyania Health, we built Synapsis AI over years of AI research, clinicians annotating data and real world tests to acutely understand and overcome every challenge at the point of care. The reason why we became obsessed with solving this problem has its roots in the very core of what is an innately human problem.

Individuals will be required to be in the office at least 4 days per week

Key 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 both 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 running inside deployments.
  • Document system designs, workflow contracts, and study definitions so new studies can be onboarded, and new engineers can ramp up quickly.

Requirements

Required Qualifications:

  • 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 (for example, 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 both SQL (e.g. MSSQL, Postgres) and NoSQL (MongoDB) data stores, including schema and query-level performance tuning.
  • Experience with containerization (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; comfortable collaborating across clinical, AI research, and frontend teams.

Nice to Have

  • Experience with Temporal or a comparable durable workflow engine (Airflow, Prefect, Argo Workflows, Cadence, Step Functions).
  • Experience orchestrating GPU-bound inference work alongside CPU-bound services in a shared-resource environment.
  • Exposure to healthcare data standards (HL7, FHIR) or EHR analytics stores (Epic Caboodle, Clarity).
  • Experience with vector databases or retrieval pipelines (pgvector, FAISS, or similar).
  • 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.

Team Culture:

  • We lead with empathy for patients and our teammates
  • We value small egos, self-awareness, and humility in our teammates
  • We appreciate flexible and adaptive attitudes towards solving problems, as strategic priorities may shift
  • We love diversity of thought, perspective, working style, skill set, knowledge, and interests amongst our team
  • We value open dialogue and brainstorming across multidisciplinary teams

Dyania Health is an equal opportunity employer that is committed to workplace diversity and inclusion. We do not discriminate on the basis of race, gender, gender identity, color, religion, national origin, sexual orientation, or any other legally protected characteristic as outlined by federal, state, or local laws.

Benefits

  • Competitive Salary
  • Training & Professional Development Support
  • Work From Home
  • Private Health Insurance
  • Daily Meals - Subsidized Meals
  • Company Laptop

Dyania operating in Greece abides by employment, PTO, public holidays, and salary structures that are in line with Greek law and local requirements.

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