Software Engineer, Abnormal AI

• 1+ years of professional development experience or 2+ years of consistent open source contributions
• Relevant software engineering experience through internships, co-ops, research, open-source work, substantial project work, or early-career full-time roles that demonstrate readiness to contribute in a production environment
• Strong software engineering fundamentals and the ability to write, test, debug, and improve production-quality code
• Experience with Python or Go, plus willingness to learn whichever language is less familiar for the role
• Familiarity with modern development workflows such as version control, code review, testing, and CI/CD
• Good judgment when using AI tools for engineering work: you can evaluate outputs, catch incorrect or incomplete solutions, and refine them to fit real system constraints
• Comfort taking ownership of scoped problems end-to-end, asking for help when needed, and steadily increasing independence
• Strong learning mindset, adaptability, and openness to feedback in a fast-moving platform environment
• Clear communication and a collaborative approach to working with teammates and internal customers

Desirable

• The Dev Accelerator team builds and operates Abnormal’s internal developer platform: the tools, libraries, and infrastructure that help engineers design, build, test, and ship products quickly and safely
• The team owns developer CLI tooling, monorepo build and CI workflows, shared Go/Python libraries, and test and release safety systems that form the Golden Path for backend development
• As a Software Engineer on Dev Accelerator, you’ll own scoped problems end-to-end with support from teammates, using good judgment and growing independence to deliver reliable outcomes
• You’ll use AI as a core part of how you explore solutions and move quickly, while validating that generated outputs are correct, maintainable, and production-ready
• Contribute to the internal developer platform that supports backend development across the company, from local developer workflows to shared services and libraries
• Build and improve scoped pieces of developer tooling, including CLI and scaffolding workflows that help engineers create and ship new services safely and consistently
• Help maintain and improve CI/CD, linting, and testing workflows in the monorepo, with a focus on reliability, fast feedback, and keeping main healthy
• Contribute code to shared Go and Python libraries and services, learning the team’s patterns for safe, maintainable, and consistent usage
• Use AI to explore approaches, automate repetitive work where appropriate, and iterate on implementations until they meet real production standards
• Debug issues, write tests, and validate behavior in real environments rather than relying only on generated output or assumptions
• Improve team documentation, examples, and shared context so both engineers and AI tools can produce better results over time