Job Description
Own the backend and cloud foundation for our applications. This role turns product requirements into secure, scalable services; guides architectural decisions; integrates AI and image-analysis capabilities; and provides technical leadership to the development team.
Key responsibilities
Evaluate the existing prototype, identify technical risks and debt, and recommend whether components should be retained, refactored, or rebuilt.
Design and implement maintainable backend services, REST or GraphQL APIs, event-driven workflows, and integration layers for web and mobile applications.
Own data architecture across relational and NoSQL stores, including schema design, migrations, indexing, performance, backups, retention, and recovery planning.
Design, deploy, and operate the backend primarily on Google Cloud using appropriate services such as Cloud Run, GKE, Cloud Functions, API Gateway, Pub/Sub, Cloud SQL, Firestore, Cloud Storage, Secret Manager, IAM, and Cloud Monitoring. Equivalent AWS experience is acceptable.
Integrate Google Gemini, Vertex AI, or comparable AI services for image-analysis workflows, including secure upload, validation, asynchronous processing, result storage, observability, and human-review paths where required.
Implement authentication, authorization, tenant isolation, encryption, secrets management, audit trails, rate limiting, input validation, and other controls appropriate for sensitive health information.
Establish CI/CD, infrastructure-as-code, automated testing, environment management, logging, monitoring, alerting, and incident-response practices.
Review code before merge, mentor less-experienced
developers, improve engineering standards, and document important architectural decisions and operational runbooks.
Work closely with the
Project Manager and product stakeholders to translate non-technical requirements into clear technical scope, dependencies, risks, and delivery estimates.
Collaborate directly with the Founders and Project Manager to assess technical feasibility, estimate delivery timelines, and translate product requirements into engineering specifications (Note: Product vision, roadmap, and feature prioritization are owned directly by the Founders
Requirements
At least 5 years of professional backend or full-stack development experience, including ownership of production systems.
Strong experience with [protected info] and TypeScript, Python, Java, Go, or a comparable backend language and framework.
Comfortable owning server and deployment operations directly - this is a hands-on role, not an architecture/lead-only position.
Hands-on experience building production workloads on Google Cloud or AWS; candidates must be comfortable with containers, Docker, networking, IAM, storage, databases, and managed compute services.
Strong API, database, distributed-systems, error-handling, performance, and observability fundamentals.
Experience integrating LLM, generative AI, machine-learning, or third-party AI APIs such as Gemini, Vertex AI, or OpenAI.
Practical knowledge of application security, secure development practices, privacy principles, and the risks involved in processing sensitive data.
Experience with Git, code review, CI/CD, automated unit and integration testing, and structured release processes.
Clear written and verbal communication, sound technical judgement, and the ability to work independently with limited senior oversight.
Preferred experience
Delivery experience in healthcare, medical technology, telehealth, diagnostics, digital health, or another regulated domain.
Experience with computer vision, image processing, medical imaging, DICOM, AI model evaluation, or human-in-the-loop review workflows.
Knowledge of healthcare interoperability standards such as FHIR or HL7 and practical approaches to consent, auditability, retention, and data residency.
Experience with Terraform or another infrastructure-as-code tool, Kubernetes, SRE practices, penetration-test remediation, and security or compliance audits.
What success looks like
The team has a clear, documented backend architecture and a realistic plan for the existing prototype.
Services are secure, observable, testable, cost-conscious, and reliable under expected workloads.
AI and image-processing features have defined quality controls, traceable results, and safe failure paths.
Developers receive timely reviews and mentoring, while technical risks are raised early and communicated clearly.