Full Stack AI Engineer

About the Team:

You will be joining a small team within Reveleer AI division, in charge of developing the next generation agentic model for clinical prospective suspecting. As a full stack software developer in our team, you will be working in the unique environment of a small team with large scale impact to enable the expansion of our product and fast growth of our users.

Responsibilities

· 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.

Required Skills

· 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.