9 months ago
Base Salary
$216k - $270k/yr
Responsibilities
- Design, develop, test, and support full-stack applications on cloud-native distributed systems.
- Build internal tools and applications, as well as tools for external customers and partners, with an approximately 60% backend and 40% frontend focus.
- Develop real-time integrations with SaaS platforms across the organization.
- Create quality frameworks and unit tests for product quality, performance, and load testing, and debug system issues.
- Build applications, Slackbots, dashboards, and automated workflows using internal and external models and platforms.
- Collaborate with the IAM team on Okta-based cloud identity and access controls for internal applications.
- Identify corporate technology service improvements and implement cross-functional self-service solutions.
- Participate in engineering council activities, conduct code reviews, and improve delivery processes.
Requirements
- At least five years of related experience with a bachelor’s degree, or equivalent work experience.
- Proficiency with React or Angular, HTML, CSS, and TypeScript.
- Proficiency with backend API development, databases, privacy permissions, Go, Python, PostgreSQL, and GraphQL.
- Experience with end-to-end testing and documentation.
- Experience developing secure, scalable, and resilient cloud applications handling sensitive data.
- Experience with AWS, Azure, GCP, Docker, or Kubernetes.
- Familiarity with SOC 2, ISO 27001, FedRAMP, and NIST compliance frameworks.
Benefits
- Comprehensive health, dental, and vision coverage.
- Retirement benefits.
- Learning and development stipend.
- Generous paid time off.
- Potential commuter stipend.
- Equity-based compensation may be available for eligible roles.
- Full-time position based in San Francisco.
Tech Stack
Categories
About Scale AI
Scale AI builds data annotation services and AI development tools for enterprises and government agencies, sold as a platform and managed services. Its products include the Scale Generative AI Platform for building and evaluating agents and the Data Engine for collecting, curating, and labeling training data, including RLHF and model evaluation. Founded in 2016 and headquartered in San Francisco, the company is privately held and works across domains from computer vision to LLM applications.