# Software Engineer, User Database Infrastructure at Notion

- Company: Notion
- What the company does: The story of its last-minute pivot and epic comeback. Backed by First Round.
- Company website: https://www.figma.com/blog/design-on-a-deadline-how-notion-pulled-itself-back-from-the-brink-of-failure/
- Type: Startups
- Level: Mid level
- Location: San Francisco, California
- Work setup: Remote
- Pay: $299K to $334K base salary per year (USD)
- Posted: 2026-09-16
- Apply by: 2026-10-31
- Apply: https://jobs.ashbyhq.com/notion/ead663e3-3eb2-4e0e-97e5-86820062dd68
- Page: https://www.1752.vc/careers/jobs/notion-software-engineer-user-database-infrastructure/

## About the role

This role will be based in San Francisco. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. You’ll build the systems that let any knowledge worker leverage fast, scalable databases without having to become a DBA.

## What they're looking for

- Strong backend engineering fundamentals. You’ve built services that need to remain correct under concurrency and failure. You can reason about retries, partial failures, consistency, and the trade-offs involved in reliable reads and writes
- A systematic approach to performance. You use query plans, traces, profiles, and experiments to find bottlenecks and verify improvements. You’re willing to follow a problem across storage, services, and client code rather than stopping at a team boundary
- Product judgment. You’re interested in who will use what you build, not just how it works. You can turn a customer’s problem into a technical approach and recognize when a better default or simpler workflow would solve it more effectively
- Willingness to work across the stack. You bring backend depth, but you’re comfortable learning unfamiliar systems and working in client code when that’s what delivering a good experience requires
- Fluency with AI-assisted engineering. You use AI to accelerate exploration, implementation, and testing while taking responsibility for understanding and validating the result

Tags: Engineering