CARPL.ai is a vendor-neutral Artificial Intelligence (AI) platform that allows radiologists to access, assess, and integrate radiology AI solutions in their clinical practice.
CARPL provides a single user interface, a single data channel, and a single procurement channel for the testing, deployment, and monitoring of AI solutions in clinical radiology workflows.
We are the world's largest radiology AI marketplace offering 250+ applications from 80+ AI vendors.
We're looking for a hands-on Software Development Engineer II (SDE II) who loves building scalable backend systems and shipping fast. You'll work closely with senior engineers and product teams to design, build, and operate cloud-native services that power our platform.
This is a high-ownership role in a fast-moving startup environmentideal for engineers who want real impact, not ticket-driven work.
What you will do:
- Build and maintain scalable backend services using Python and Java.
- Develop microservices and event-driven systems on AWS and GCP.
- Design and consume RESTful APIs and asynchronous workflows.
- Own features end-to-endfrom design to production deployment.
- Improve system performance, reliability, and scalability through debugging and optimization.
- Work closely with product, DevOps, and QA to ship features quickly and safely.
- Participate actively in code reviews, design discussions, and on-call rotations.
- Contribute to clean code, testing, and security best practices.
What we are looking for:
- 35 years of hands-on backend development experience.
- Strong proficiency in Java.
- Experience building backend or microservices-based systems.
- Solid experience with AWS and/or GCP (EC2, S3, Lambda, ECS, Cloud Run, Pub/Sub, etc.).
- Good understanding of distributed systems, APIs, and async processing.
- Experience with relational and NoSQL databases (PostgreSQL, MySQL, DynamoDB, MongoDB).
- Working knowledge of Docker; exposure to Kubernetes is a plus.
- Familiarity with CI/CD pipelines and production deployments.
- Strong problem-solving skills and a bias for action.
- Comfortable in a fast-paced, ambiguous startup environment.
