Software Engineer

Who you are

• Strong backend engineering fundamentals, with interest in performance, reliability, scalability, and systems that need to hold up under real customer load
• Curiosity about distributed systems, microservices, and data-layer trade-offs; experience in these areas is helpful, but we care most about your ability to learn quickly and reason from first principles
• Practical comfort with JavaScript or TypeScript, or the ability to ramp quickly in a codebase where those tools matter
• Grit and truth-seeking in technical problem solving: you can iterate when the first approach does not move P50/P95 performance, and you’re motivated by finding the real bottleneck
• A self-guided learning style: you use docs, code, teammates, and AI to build context, ask better questions, and turn ambiguity into steady progress
• If you’re excited about this role but don’t meet every bullet, we still encourage you to apply

What the job involves

• As a Software Engineer on Collections Infra, you’ll help scale the infrastructure behind Notion’s database block. Databases power views, boards, charts, forms, and the workflows customers use to run their companies; as Notion grows into larger enterprise deployments and AI-native work, those systems need to become faster, more reliable, and ready for much higher concurrency
• This team sits between infrastructure and product, building backend architecture that improves the customer experience while becoming a platform other Notion teams can build on
• You’ll work on problems like database load performance, microservices, high-volume writes from agents, and the flexibility that makes Notion databases powerful and hard to scale
• By your 90th day, you’ll understand how Collections Infra supports Notion’s database block, ship improvements to database performance or reliability, and build context on the scale challenges behind larger enterprise workspaces and AI-driven write volume
• You’ll use AI as a real engineering collaborator: to learn unfamiliar systems faster, explore debugging paths, generate tests, summarize traces or logs, and pressure-test implementation plans before shipping
• You’ll contribute to the team’s work to make databases faster and more reliable at P95 scale, especially as customers build larger centralized databases with more concurrent usage
• By the end of your first year, you’ll have helped raise the quality bar for Collections infrastructure through better architecture, observability, documentation, or system boundaries that make future work easier to build on
• You’ll partner with senior engineers and product-facing teams to evolve Collections as a platform, balancing internal developer needs with the external customer experience of databases