Ampa
Backend Engineer – APIs & Data Systems
Palo Alto, CA
No sponsorship$130k-$220kDetected 19 days ago
TypeScriptPythonNode.jsPostgreSQLAWSAPI DevelopmentGraphQLRESTData EngineeringLogisticsCollaborationAdaptability
About the role
- You'll take ownership of our backend architecture - from designing efficient data models to managing API integrations with our web, mobile, and embedded systems.
- Tech Stack: Languages: Python, Node.js (TypeScript) APIs: REST, GraphQL Database: PostgreSQL (hosted on AWS RDS) Cloud: AWS (ECS, Lambda, EventBridge, S3) Key
Responsibilities
- Effective: Learns fast, adapts quickly, and consistently delivers results.
- Build and maintain REST and
- Build and support
- Create or manage data pipelines for aggregating patient session data and system logs
- Ampa is a pioneering neurotechnology startup developing brain stimulation technology to help eradicate depression.
Requirements
- Extensive experience with PostgreSQL, particularly on
- Familiarity with
Skills
- Driven: Highly motivated and resilient.
- Growth: Thrive in a startup environment with rapid innovation.
- Stability: Enjoy startup benefits with a secure product line.
- Languages: Python, Node.js (TypeScript)
- PostgreSQL (hosted on
Compensation
- $130K - $220K · 0.4% - 1%
Benefits
- Joining us means you'll be part of a rapidly growing startup with significant equity opportunities and a major impact on our future.
- Lead the development of transformative mental health technologies.
- Receive substantial equity as an early team member.
- We're looking for an exceptional Backend Engineer to build the secure, scalable APIs and data systems that power our clinical platform and medical devices.
- $130K - $220K · 0.4% - 1% Equity Employment: Permanent
- Working at Ampa is a rare chance to help transform global mental health and save millions of lives - a level of impact that demands deep commitment.
Visa & Work Authorization
- Will sponsor TN visa or equivalent.
This listing is sourced directly from Ampa's careers page and normalized into a canonical job model.