Engineering Intern

Who you are

• Currently pursuing a B.S. in Computer Science or related technical field, graduating between 2027 and 2028, with coursework or project experience in software engineering
• You use AI to learn faster, debug, and ship, and can point to something you've built with it
• You dig into a problem before waiting for someone to hand you the answer, and you ask for help once you're stuck, not before you've tried
• Proficient in one or more of JavaScript, TypeScript, Ruby, or Kotlin, with real project experience beyond coursework
• Comfortable picking up new frameworks and tools quickly, ideally with some exposure to React, Postgres, SQL, or gRPC
• Strong problem-solving instincts and equally comfortable working independently or pairing with a teammate
• Clear, direct communicator who can explain technical tradeoffs to both engineers and non-engineers
• Available to work in person from our Union Square, NYC office

What the job involves

• As we continue to expand our reach and impact, we are seeking highly motivated and talented engineering interns to join our team for Summer of 2027
• Duration: June 2027 to August 2027
• This internship puts you inside a live engineering team shipping product that hundreds of thousands of service businesses and their clients touch every day. You'll work on real features headed to production, not a side project built to keep you busy. Genius AI is scaling an agentic product at a pace where decisions ship in days, and this role exists so you get real exposure to how that speed and judgment work together
• You will report to an engineering manager on our team
• Build and test features for our web and mobile products alongside senior engineers, shaping experiences used by our customers and their clients
• Architect small pieces of automation with AI, not just use it as an assistant: identify repeatable work in your own project and build the system that removes it
• Write clean, efficient code that meets Genius AI engineering standards, and own debugging and troubleshooting
• Partner with data analysts to collect and interpret usage data, and use those insights to inform how AI gets applied across the product
• Ship fast, learn faster: iterate on your projects with AI-assisted development on a tight cadence, adjusting based on feedback from senior engineers
• Expand your technical range deliberately, picking up new languages, frameworks, and AI-native development practices as the team's needs shift