Snap
Software Engineer, Full Stack, Level 4
$133K–$235K
Los Angeles, California +4 · Full-time · Posted Oct 21, 2026
- Location
- Los Angeles, California
San Francisco, California
Palo Alto, California
New York, New York
Bellevue, Washington - Experience
- 2+ years of post-Bachelor’s software development experience; or a Master’s degree in a technical field plus 1+ year of post-grad software development experience; or a PhD in a relevant technical field.
- Education
- Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience.
About the job
Build and optimize full-stack web applications and services for Snap’s user-facing products, using AI tools while maintaining code quality, security, and performance.
What you'll do
- Build mobile and desktop web applications and systems, including features and user interfaces.
- Follow strong design and implementation practices and contribute to shared libraries and systems.
- Analyze operational and engagement metrics and use AI-assisted workflows to develop scalable services.
What they ask for
- Proficiency in JavaScript and/or TypeScript, HTML, CSS, and one or more of Java, Golang, NodeJs, or Python.
- Experience with a JavaScript UI framework such as React, Angular, or Vue, and with full-stack web development.
- Knowledge of object-oriented and functional programming, domain-driven design, and unit testing.
- Bachelor’s degree in a relevant technical field or equivalent practical work experience; required software development experience as detailed below.
Nice to have
- Experience with advanced front-end technologies, GraphQL, microservices, or distributed systems.
- Experience with NoSQL, Memcache/Redis, Kubernetes, Google/AWS services, and performance or scalability optimization.
Pay
USD $157,000-$235,000 annually (base salary); USD $149,000-$223,000 annually (base salary); USD $133,000-$200,000 annually (base salary)
Tools
JavaScript, TypeScript, HTML, CSS, Java, Golang, NodeJs, Python
AI focus
Use AI tools to streamline development and ship scalable services; evaluate generated code for architectural integrity, performance bottlenecks, and security risks, and adapt to evolving AI tools.
Model-written summary · the original posting is authoritative