Software Engineer Intern

The Software Engineer Intern builds production software in an AI-first workflow, working under the guidance of senior engineers. The role spans the full software development lifecycle—from specification and implementation through review, testing, and deployment—while collaborating with Product Analysts, Project Managers, Product Architects, and fellow engineers. The intern is expected to take full ownership of the code they ship, including AI-generated contributions, and to verify and defend every line for correctness, security, and reliability.

Responsibilities

• Design, develop, and deploy scalable and reliable software solutions under the guidance of senior engineers
• Write clean, reusable, and maintainable code aligned with industry standards and organizational guidelines (typed or generated)
• Use AI coding assistants and agents as a normal part of daily development work
• Break work into units specific enough for an AI tool to execute well, then verify results rather than assuming correctness
• Take full ownership of AI-generated code, including explaining and defending every line in review
• Recognize and mitigate common failure modes in AI-generated code (e.g., hallucinated APIs, insecure defaults, dropped edge cases, incorrect logic that appears correct)
• Develop judgment about when not to use AI when a problem is faster, safer, or clearer solved by hand
• Review and improve code for functionality, efficiency, security, and scalability
• Participate in sprint planning, daily stand-ups, retrospectives, and reviews with cross-functional partners and engineers
• Assist in automating development, testing, deployment, and monitoring processes to improve operational efficiency
• Maintain documentation for code, processes, and best practices, including context files, specs, and repository conventions that help AI tools work effectively
  
  

Required Qualifications

• Currently pursuing or recently completed a degree in Computer Science, Information Technology, Software Engineering, or a related field
• Hands-on experience using AI coding assistants in personal or academic projects, with the ability to explain what the generated code actually does
• Basic understanding of software development and the SDLC
• Knowledge of version control tools such as Git or GitHub
• Exposure to web or mobile app development, front-end or back-end
• Experience with unit and integration testing
• Strong problem-solving skills and ability to collaborate in a team-oriented environment
• Available for at least 3 months with a minimum of 6 hours of daily work commitment
  
  

Preferred Qualifications

• Experience calling LLM APIs directly in a project of their own
• Experience writing evaluations or test harnesses for non-deterministic output
• Familiarity with frameworks such as Flutter, React, NestJS, Angular, or Django
• A project they can walk through and honestly attribute (which parts were AI-built vs. built by them, and where they overrode AI)
• Interest in software products, digital banking, or technology