Software Development Engineer Intern - File System Service

About the role

Autodesk is looking for a Software Development Engineer Intern to work alongside the engineering team on the development, maintenance and operation of the File System Service. The intern applies Specification Driven Development (SDD) and agentic AI workflows to build and improve service capabilities, including APIs such as GraphQL, while keeping the service reliable and operational. The internship runs from 11 January to 25 June 2027 (6 months full time, fixed dates) and is based in Singapore; an in-person recruitment drive runs from 9 October to 6 November 2026.

Key responsibilities

• Develop and enhance the File System Service, including API-related features
• Maintain and keep the service reliable through bug fixing and addressing technical debt
• Apply Specification Driven Development to implement, validate and verify software changes
• Use and develop agentic AI workflows to automate engineering tasks, solve operational problems and improve efficiency
• Improve personal productivity with AI in research, writing, analysis and software development
• Collaborate with engineers to deliver production-relevant capabilities and improve engineering practices

Required profile

• Currently enrolled in a Bachelor's degree in Computer Science, Computer Engineering or a related field, graduating in 2027 or 2028
• Strong written and verbal communication skills in English
• Preferred: strong problem-solving skills, ability to work with complex software systems and in a dynamic, collaborative environment

Required skills

• Strong programming skills, preferably in Java and/or Python
• Preferred: exposure to cloud platforms such as AWS, Azure or GCP, and experience with SQL and/or NoSQL data stores

What we offer

• Hands-on experience developing, maintaining and operating a production-relevant backend service
• Work alongside engineers on real product features, maintenance and operational challenges
• Experience applying Specification Driven Development and agentic AI workflows in day-to-day engineering