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# Full Stack AI Engineer

- **Company:** Health Data Vision, Inc.
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Artificial Intelligence, Airflow, Amazon Web Services, Architectural Patterns, BigQuery, Cascading Style Sheets (CSS), Clinical Data Repository, Cloud Engineering, Distributed Systems, Python (Programming Language), Node.Js, TypeScript, Google Cloud, ReactJS, Large Language Models, Backend, Event Driven Architecture, Containerization, Front End Software Development, Data Pipelines, Microservices
- **Published:** August 10, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f8ccd803cc0c35ab

## About the Role

* 5+ years of experience building high-quality code and infrastructure.
 * 3+ years of experience working with large-scale distributed systems - microservices, event-driven architecture, or pipeline orchestration.
 * 2+ years of experience with AWS or Google Cloud.
 * Hands-on experience building across the stack: backend services (Python, Node, or similar) and frontend interfaces (React, TypeScript, CSS).
 * Familiarity with containerization, cloud-native deployment patterns, and common architectural patterns for scalable systems.
 * Strong debugging instincts - you can trace a problem through multiple services, read logs, form hypotheses, and fix things under pressure without relying on an LLM to do the thinking for you.
 * Proven curiosity with the latest generative AI advances and a thoughtful perspective on where AI tools help and where they don't.
 * High ownership and accountability. You treat the systems you build as yours

Nice to Have

 * Experience in healthcare, clinical data, or value-based care.
 * Experience with pipeline orchestration tools (Airflow, Prefect, Dagster, or similar).
 * Experience with Firestore, BigQuery, or other GCP data services.

## Description

* Apply first-principles thinking to break down hard problems and ship durable solutions.
 * Understand business needs and build end-to-end product experiences across the stack - backend services, data pipelines, and frontend interfaces.
 * Build, scale, and maintain infrastructure - containerized microservices, orchestration pipelines, cloud-native architecture.
 * Develop and continually improve observability of systems and infrastructure at scale.
 * Partner closely with clinical experts and other engineers to build highly scalable, clinically accurate systems that surface actionable insights.
 * Challenge the status quo. If something is slow, fragile, or over-engineered, fix it.
 * Troubleshoot, diagnose, and resolve production issues daily. Own the problem from alert to root cause to prevention.


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