Drimva

Snap

Software Engineer, Backend, Level 5

$178K–$313K

Los Angeles, California +4 · Full-time · Posted Oct 1, 2026

Location
Los Angeles, California
San Francisco, California
Palo Alto, California
New York, New York
Bellevue, Washington
Experience
6+ years post-Bachelor’s; or Master’s + 5+ years post-grad; or PhD + 2+ years post-grad software development experience.
Education
Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience.

About the job

Designs, builds, and operates Snap’s critical backend services, collaborating across teams to deliver scalable products with strong operational, security, and quality standards.

What you'll do

  • Design, implement, and operate critical services such as user identity, friend graph, and core persistence.
  • Evaluate, test, and debug work while applying best practices for availability, scalability, operational excellence, and cost management.
  • Use AI tools and high-velocity engineering workflows to ship scalable services while ensuring code correctness, security, and production readiness.

What they ask for

  • Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience.
  • Experience with distributed systems.
  • Proven track record of operating highly-available systems at significant scale.
  • 6+ years of post-Bachelor’s software development experience; or Master’s degree in a technical field + 5+ year of post-grad software development experience; or PhD in a relevant technical field + 2+ years of post-grad software development experience.

Nice to have

  • Experience with Java, C++, and/or Python.
  • Experience with NoSQL solutions, Memcache/Redis, Kubernetes, or Google/AWS services.

Pay

$209,000-$313,000 annually (Zone A; base salary); $199,000-$297,000 annually (Zone B; base salary); $178,000-$266,000 annually (Zone C; base salary)

Tools

Java, C++, Python, NoSQL, Memcache/Redis, Kubernetes, Google/AWS services

AI focus

Use AI tools to streamline backend development and ship scalable services; audit generated output for architectural integrity, performance bottlenecks, and security risks, and adapt to evolving AI systems and tools.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 4, 2026 (UTC)