About the Role
The role involves leading development efforts on a product-integrated AI platform, focusing on full stack implementation, system architecture, and collaboration with design and research teams to deliver intelligent features.
Responsibilities
- Design and implement backend services using Ruby on Rails
- Develop responsive user interfaces with React and modern JavaScript
- Collaborate with product managers to define feature requirements
- Integrate machine learning models into production workflows
- Optimize application performance and scalability
- Write clean, maintainable, and well-tested code
- Lead code reviews and contribute to engineering best practices
- Troubleshoot and resolve technical issues in production
- Work closely with data scientists on AI feature development
- Maintain and improve CI/CD pipelines
- Ensure application security and data privacy standards
- Participate in architectural planning and technical decision-making
- Mentor junior engineers and support team growth
- Monitor system reliability and respond to incidents
- Evaluate new technologies for potential integration
- Contribute to documentation and internal knowledge sharing
- Support deployment and infrastructure improvements
- Refactor legacy components for better maintainability
- Implement analytics and tracking for product insights
- Ensure cross-browser and cross-device compatibility
- Follow agile development methodologies
- Deliver end-to-end features from concept to launch
- Improve accessibility standards in front-end components
- Collaborate on API design and versioning
- Balance technical debt with product delivery timelines
Compensation
Competitive salary and equity package
Work Arrangement
Fully remote with flexible hours
Team
Small, autonomous product team focused on AI-driven features
Why This Role Stands Out
- Work directly on AI-integrated product features with real user impact
- Opportunity to shape technical direction in a growing engineering team
Tech Stack
Ruby on Rails, React, PostgreSQL, AWS, Docker, Kubernetes, Python (for ML integration)
Application Process
- Submit resume and GitHub profile
- Initial screening call with hiring manager
- Technical interview with engineering team
- Final interview with product and tech leads
Available for qualified candidates
