Mid/Senior Backend Engineer

Dyania Health is a venture-backed company founded in 2019 which has developed Synapsis AI, an end-to-end platform that combines a medically pre-adapted LLM with a physician-driven algorithmic reasoning engine to understand and assess clinical characteristics in electronic medical records. Synapsis AI is designed for installation within a healthcare system's computing environment to automate the process of manual chart review of electronic medical records, without removing any data from the healthcare system. Synapsis AI completes pre-screening on both unstructured and structured patient data and deploys medical logic with temporal sensitivity to match dynamically changing patient characteristics with complex clinical trial criteria during the exact window of time that a given EMR may qualify for study protocol criteria.

We are looking for Backend Software Engineers to join our growing team in Athens, Greece. This role focuses on two complementary tracks: (1) authoring and maintaining the study-specific code that encodes clinical logic, and (2) building and hardening the event-driven backend that orchestrates the Synapsis AI platform for screening across hospital data environments. The ideal candidate has experience with event-driven and workflow-based systems, large-scale data processing, and Python services that integrate heterogeneous clinical data sources into a unified pipeline.

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.

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.

• 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.

• 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

Benefits

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