Software Engineer, Database Infrastructure

Superhuman offers a dynamic hybrid working model for this role. This flexible approach gives team members the best of both worlds: plenty of focus time along with in-person collaboration that helps foster trust, innovation, and a strong team culture.

Grammarly is now part of Superhuman, the AI productivity platform on a mission to unlock the superhuman potential in everyone. The Superhuman suite of apps and agents brings AI wherever people work, integrating with over 1 million applications and websites. The company’s products include Grammarly’s writing assistance, Coda’s collaborative work spaces, Mail’s inbox management, and Go, the proactive AI assistant that understands context and delivers help automatically.

Founded in 2009, Superhuman empowers over 40 million people, 50,000 organizations, and 3,000 educational institutions worldwide to eliminate busywork and focus on what matters. Learn more at  and about our values here.

We're looking for a Software Engineer to join the Platform team within Superhuman Docs. This is an opportunity to work on and grow into a technical leadership role on the foundation that powers every table, grid, and view on the platform.

Superhuman Docs is where teams build living documents that replace scattered tools with a single, flexible surface. At the heart of this experience is the table the building block that makes a doc feel like a real application. Tables aren't passive containers; they support rich filtering, a diverse and extendable set of data types, multi‑column sorts and groupings, external database sync, and relational dependencies.

Every cell change flows through a distributed sync engine and must land consistent across every collaborator, view, and dependent formula. This problem is harder than building a general‑purpose database because of who the users are. Our customers aren't database administrators — they're teams who opened a doc to build a tracker or CRM and ended up running a real application.

That means managing an enormous number of distinct databases — most of which go cold over time but none of which we can delete — requiring cost‑aware architectural choices. We have to support enterprise‑grade encryption that the major cloud providers don't offer out of the box. We need a system that stays performant under access patterns that can shift at any moment — and invisible to customers who shouldn't have to think about any of it.

• Contribute to — and grow into technical leadership on — the structured data storage layer, including cell storage, row ordering, index management, view materialization, and query execution.
• Help drive improvements to how the platform handles large, complex tables at scale: lazy hydration strategies, data compaction, cache invalidation, and the lifecycle of cell data through the sync pipeline.
• Work on server‑side query planning for database‑backed tables — pushing filter, sort, and grouping operations closer to the data layer and away from the client.
• Collaborate with the formula engine and sync teams to ensure correctness at the boundaries: formula dependency tracking, column state transitions, and consistent view state across concurrent operations.
• Contribute to performance benchmarking and profiling practices for table operations, giving the team observable data to drive storage and query optimization decisions.
• Raise the technical bar across the team — reviewing designs, mentoring engineers, and bringing database internals thinking to problems the team is actively working through.
• Help define how structured data evolves on Superhuman Docs — anticipating the demands of cold storage tiers, per‑tenant encryption at scale, unpredictable access patterns, and the flexibility requirements of a general‑purpose application platform.

• 8+ years of industry experience and at least 5 of those working on relevant technologies.
• Has deep experience building or substantially contributing to the internals of a storage or database system — query execution, index management, storage engines, or transaction/consistency layers in systems like Postgre
  
  SQL, MySQL,…