Our client is seeking a backend engineer to assume full responsibility for core functionalities on their medical imaging platform. In this role, you will not just hand off your code at the pull request stage but will be directly accountable for system accuracy, production stability, and the security of clinical data that impacts patient care directly.

The data science team creates machine learning models; your task is to create the robust, deterministic platform that supports them. Your responsibilities will include designing scalable architectures, resolving concurrency issues, ensuring seamless data migrations without downtime, and ensuring the stability of legacy services as their replacements are developed.

Responsibilities:

Full ownership of the technical roadmap of our Python/FastAPI ecosystem, encompassing API design, background task distribution, and production observability.
Manage and develop our PostgreSQL schema in terms of data integrity and persistence, including migrations, lock mechanisms, query optimization, and multi-tenant data isolation while adhering to HIPAA/PHI compliance.
Design and implement resilient image processing pipelines for handling intensive medical imaging files in asynchronous, event-driven workflows from ingestion and de-identification to model inference and result delivery.
Establish reliable API interfaces with frontend teams and clear model input/output contracts with data scientists to ensure a smooth cross-functional collaboration.
Keep thorough technical records, oversee the transition of legacy systems, and maintain Architecture Decision Records (ADRs).

Requirements:

Minimum of 5 years of software engineering experience with demonstrated production ownership and deep expertise in systems and backend fundamentals.
Proficiency in concurrency and distributed systems with a strong understanding of race conditions, deadlocks, idempotent processing, and messaging failure modes.
Hands-on experience with PostgreSQL internals and message brokers in a production environment.
Strong commitment to typed code, automated testing, CI/CD pipelines, Docker, and modern AI developer tools.
Ability to challenge requirements, set technical standards, and communicate effectively in both English and Chinese.

Nice-to-have Skills:

Familiarity with operating containerized workloads on Google Cloud Platform.
Direct experience with medical imaging workflows, DICOM standard protocols, or healthcare regulatory frameworks.
Knowledge of multi-tenant database patterns or deploying hybrid cloud/on-prem solutions.
Exposure to scientific computing contexts like NumPy, computational geometry, or frontend technologies like React/TypeScript.

Certain AI tools may be utilized in the hiring process for tasks such as application review and assessing candidate materials. These tools assist but do not replace human judgment, with final hiring decisions being made by humans. For more information on data processing, please contact us directly.

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