Eulerity
Backend Developer Intern
About this role
Eulerity seeks a Backend Developer Intern to develop and maintain backend services for their marketing automation platform, with a strong focus on leveraging AI agents and LLMs to accelerate development. You'll work on feature implementation from design to deployment while collaborating cross-functionally in a hybrid NYC-based role.
What you'll do
- Develop, test, and maintain backend services using AI agents to enhance productivity
- Implement new features from design through deployment
- Generate product ideas and prototype solutions using AI tooling
- Collaborate with cross-functional teams on features and releases
- Create documentation and provide system support
- Integrate third-party APIs into backend solutions
What they're looking for
- Java backend development (1+ years)
- AI agents and LLM frameworks (Claude, Copilot, Cursor)
- AI-assisted software development and debugging
- Third-party API integration
- Problem-solving and creative thinking
- Code review and peer collaboration
- Technical documentation
- Communication skills
Benefits
- Hourly compensation of $17–$19
- Mentorship with regular peer review sessions
- Full GitHub Copilot access and frontier LLM tools
- Unlimited snacks and in-office lunch credit
- Hybrid work flexibility with one day on-site weekly
- Potential extension beyond August based on performance
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Eulerity
Eulerity builds an AI-native marketing automation platform that helps enterprise and franchise clients streamline multi-location marketing operations through APIs, SDKs, and integrated workflows. The company is hiring across web development, iOS engineering, solutions engineering, and forward-deployed roles to expand its platform capabilities and customer success.
- Website
- eulerity.com
Likely interview questions
- Describe a specific project where you used an AI coding agent like Claude or Copilot to build, debug, or improve backend code—what was the outcome?
- How do you approach using LLMs to solve complex engineering problems, and what's your process for reviewing AI-generated code?